water testing research paper

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• Am J Trop Med Hyg
• v.87(1); 2012 Jul 1

The Effect of Water Quality Testing on Household Behavior: Evidence from an Experiment in Rural India

Associated data.

How does specific information about contamination in a household's drinking water affect water handling behavior? We randomly split a sample of households in rural Andhra Pradesh, India. The treatment group observed a contamination test of the drinking water in their own household storage vessel; while they were waiting for their results, they were also provided with a list of actions that they could take to remedy contamination if they tested positive. The control group received no test or guidance. The drinking water of nearly 90% of tested households showed evidence of contamination by fecal bacteria. They reacted by purchasing more of their water from commercial sources but not by making more time-intensive adjustments. Providing salient evidence of risk increases demand for commercial clean water.

Introduction

When people receive new information about health risks, they may change their behavior to protect themselves. However, the benefit of risk reduction is often less salient than the costs of behavior change, and therefore, information alone may be insufficient as a motivator. Rigorous experimental research has begun to shed light on this question. 1 – 11 Recent field experiments have informed households in underresourced communities about microbial contamination in their drinking water and tested whether that information motivated a change in behavior. The emerging evidence is that, on average and in many different contexts, it may. 9 , 12 We extend this body of knowledge by using an innovative study design to explore two related questions. First, when reacting to information about contamination, how do households trade off cash-intensive versus time-intensive risk avoidance strategies? Second, do response strategies vary across the socioeconomic distribution? We randomized credible and salient household-specific information about drinking water contamination to about one-half of 1,940 sample households in 44 villages in rural Andhra Pradesh, India; the other one-half of the sample served as a control group. The water quality information was provided through the use of test kits that detect hydrogen sulfide-producing fecal coliform bacteria. While waiting for their test results, householders were given specific suggestions of both cash- and time-intensive actions that could be taken to address a positive result.

Intervention.

This study tested the effect of an intervention that combined household-specific water quality information with messages about steps that households could take to improve it. At the end of a baseline survey about water, sanitation, and hygiene behaviors, approximately one-half of 1,940 study households (931 in all) had their drinking water tested for fecal contamination. Enumerators then read an informational handout to respondents that explained how to interpret test results and how to improve water quality; the handout was left with the respondent household at the end of the visit. The following behaviors were recommended: (1) obtain drinking water from safe sources such as a community water supply (CWS) or bottled water; (2) chemically treat, boil, or use advanced filters; and/or (3) use a series of cheaper but more time-intensive compensatory strategies (like avoiding direct hand contact with water and keeping water out of the reach of children).

Tests of water from each treatment household's primary in-house drinking water storage container were conducted using H 2 S test kits from HiMedia. The tests are inexpensive, costing less than $0.50 per kit. The HiMedia test kits (HiMedia Laboratories Pvt Ltd., Mumbai, India) detect hydrogen sulfide-producing fecal coliform organisms and were modified to also detect Escherichia coli and Salmonella typhimurium . Contaminated water turns black within 48 hours; in addition, opening the bottle with such a positive (black) test result releases a strong odor that smells like rotten eggs. Intervention materials stated clearly that a positive test outcome implies contamination and a potential health risk, but it does not mean that consuming the water will necessarily make one sick. 13 , 14 One kit was left with the tested household, and another kit was retained by study personnel.

Study design.

The research used a randomized design to study the effect of information provision on treatment households. Power calculations suggested that a sample of approximately 50 households from each village would be more than sufficient to show a change in household behavior. Using a random number generator, we identified 25 households that would receive the water test and associated behavior change messages and another 25 households that would serve as controls.

Sampling frame.

The villages in the study were chosen from communities that had participated in an earlier study in 2006 examining the impacts of advanced CWS systems in three districts of Andhra Pradesh. 8 Study villages had (1) populations of at least 2,200 people, (2) a perennial surface water source that was not chemically contaminated, and (3) successful mobilization to finance a down payment for the investments in treatment infrastructure. Respondent households in this previous study were a representative sample of households with children under the age of 3 years. The evaluation of that intervention had revealed low sustained purchase of commercial safe water from the CWS centers and found that availability of CWS systems had no impact on health or water quality outcomes. 8

This study was conducted in 44 villages that had participated in the 2006 study. They were located in Krishna, Guntur, and West Godavari districts in central coastal Andhra Pradesh, India.

Survey implementation and interview procedure.

Household survey instruments were designed based on existing questionnaires, literature reviews, and inputs from local advisors and study partners. Survey instruments were translated into Telugu and refined based on focus group discussions and pretests in villages in Andhra Pradesh. Trained enumerators and field supervisors with at least high school education carried out the field work. Baseline data collection and water testing took place in December of 2010, and the second round of surveys took place 1 month later in late January and early February of 2011.

The survey instrument consisted of questions and enumerator observations on water source availability; transport, storage, and handling; averting behaviors; exposure to sanitation and hygiene messages; and household demographics and socioeconomic characteristics. Survey responses were obtained from a male or female adult in each sample household. Informed consent was obtained from all respondents; survey protocols were approved by the institutional review board of Research Triangle Institute International.

The randomized design of this experiment allows for straightforward analysis and reporting of survey results. Furthermore, the rich data from the previous intervention can aid and motivate more nuanced understanding of the evolving context in these communities. In the results, we present descriptive statistics for key household characteristics and behaviors as well as prior experience with water testing grouped by treatment assignment in the baseline survey in 2010. This comparison allows assessment of the quality of the randomization procedure. An array of characteristics is shown to be balanced between treatment and control groups, suggesting that our randomization algorithm produced exchangeable groups as intended.

We then analyze the impacts of our intervention on several key water and hygiene-related outcomes. These outcomes include sourcing of water from a CWS as well as hygiene and safe water handling practices. We estimate impacts using a simple difference in means between treated and control households as well as the more conservative difference in differences (DiD) estimator that takes into account any baseline differences between these two groups that could have arisen solely as a result of chance. The DiD estimator is conservative because it subtracts the difference in means between treatments and controls at baseline (although this difference is zero in expectation) from the difference in treatments and controls at follow-up. This strategy is equivalent to a comparison of baseline to follow-up trends in the two groups, and therefore, it sweeps out the effects of any common changes over time that may be occurring in the background. 3 , 8 It is obtained using the following linear regression, with relevant outcomes y it on the left-hand side and indicators of treatment assignment T i , a dummy 2011 it that is equal to 1 for the follow-up study wave and 0 during the initial study wave, and an interaction of the two variables on the right-hand side:

Also, several outcomes are measured on an ordinal scale—for example, respondents were asked how often they wash their water vessels, with possible answers on a five-point scale (1 = every day, 4 = rarely, 5 = never). To analyze impacts on these outcomes, we use an ordered logit regression to compare the odds of moving between ordinal categories among control and treatment households. In those analyses, our DiD estimator represents a ratio of odds ratios.

Table 1 presents baseline statistics for the two experimental arms and tests for differences. Although only about 14 characteristics are shown in Table 1 , we examined a total of 75 baseline characteristics (those characteristics not shown in Table 1 appear in Supplemental Table 1). Treatment households were not statistically different from control households in 70 of 75 characteristics (at the 10% confidence level). Apparent sample imbalances are not consistent across different measures of similar constructs—for example, control households were 2.5% more likely to have a literate adult (difference not statistically significant), although they were measured to be slightly less educated (significant at 10% confidence). We interpret this finding as an indication that the few statistically significant differences between the arms at baseline are merely rare results of simple chance. We conclude that the randomization was successful in establishing balance in terms of observed—and also unobserved—characteristics. Nonetheless, as an added precaution, we present the results of a DiD estimator to supplement our simple comparisons of changes in mean outcomes, and therefore, conservative readers can see the differential change in household behavior between the two arms during the month of follow-up.

Household characteristics and behaviors in the baseline

With the exception of the rows labeled demographics and socioeconomic indicators (which indicates mean counts of adults and children in treatment and control households), each row represents a binary variable; each cell in control and treatment columns represents the percentage of households who have the characteristic indicated in the row title. The 1,940 households represented were all successfully interviewed at baseline in 2010.

HH = household.

The results that we present here represent an intent to treat (ITT) approach—comparing behavior change among the treatment group with the change among the control group regardless of the test result. In fact, the contamination test was positive in 88% of tested households. Given the overwhelming prevalence of contamination, we interpret these results as a reasonable lower bound on the impact of credible information on contamination. In analyses not reported here, we have also restricted our treatment group to only the 88% that tested positive; the patterns are consistent with those patterns that we report here, although the effects are somewhat stronger. The ITT results are much easier to interpret because they are not influenced by potential confounding factors that affect both test results and behavior change.

Tested households also received explicit advice on specific behaviors that they could undertake to reduce their risk of contamination. Most were time-intensive (for example, washing hands more frequently), but two were cash-intensive (purchasing water from commercial purification centers and purchasing more modern storage and transport containers).

Tables 2 and ​ and3 3 illustrate the impact of the information on water sourcing. At baseline, about equal fractions of treatments of treatment and control households were purchasing water from commercial suppliers (95% confidence interval [CI] = –3.3 to 2.2; P > 40%) ( Table 2 ). This finding indicates that the randomization worked properly to establish similarity between the groups at baseline; however, by follow-up, nearly 5% more households were purchasing water from commercial suppliers (95% CI = 1.9–7.5; P < 0.1%) for a total DiD of 5.3% (95% CI = 2.3–8.3; P < 0.1%). An alternative way to compute the same DiD would be to compare the differential time trends between the two groups ( Table 3 ). Within the treatment group, the fraction of households relying on commercial suppliers rose by 3% (95% CI = 1.0–5.3, P < 1%); among the control group, this fraction declined by 2.3% points (95% CI = –4.3 to –0.1, P < 5%), and adding these values will generate the DiD (5.3%). Given that only 10% of households were purchasing such water at baseline, this finding represents an increase in the likelihood of purchasing treated water by a factor of 1.5. Consistent with these findings is the fact that tested households were more likely to change the mode of transport that they used to fetch water (results not shown). Table 3 provides a more complete picture of how treatment households adjusted their primary water sourcing between the waves—shifting away from (zero cash marginal cost) taps and private wells and to (costly) commercial safe water. In contrast, control households were shifting away from commercial safe water ( P = 0.05). This pattern of shifting to cash-cheaper alternatives is consistent with other research that finds households diverting their efforts away from diarrheal disease-averting behaviors as the monsoon season wanes and perceived risk declines. 7 , 15

Difference in water sourcing between tested and control households at baseline and follow-up

Each row represents a separate linear probability regression using regression equation 1 in the text. The sample underlying this table comprises the 1,940 households interviewed in 2010. The 76 households that were lost to follow-up are grouped into the other (including missing) category. The water sources represented in the rows are mutually exclusive and communally exhaustive, but the columns may not sum exactly to zero (and column 5 does not sum exactly to 100%) because of rounding. All coefficients and 95% CI limits (shown in parentheses) are multiplied by 100 to represent marginal effects in terms of percentage points.

Difference in water sourcing between tested and control households at baseline and follow-up: Changes in reliance on each water source between baseline and follow-up

Each row represents a separate linear probability regression using regression equation 1 in the text. The sample underlying this table comprises the 1,940 households interviewed in 2010. The 76 households that were lost to follow-up are grouped in the other (including missing) category. The water sources represented in the rows are mutually exclusive and communally exhaustive, but the columns may not sum exactly to zero because of rounding. All coefficients and 95% CI limits (shown in parentheses) are multiplied by 100 to represent marginal effects in terms of percentage points.

Households in the control and treatment groups showed much less evidence of differences in terms of cash-cheaper but more time-intensive adjustments. As shown in Table 4 , treatment households were significantly more likely at follow-up to use a tap or ladle to extract water from storage containers and have tight screw caps on storage containers. Similarly, the DiD estimates show that such households were 1.2% more likely to use recommended in-house treatment methods, were 1.4% more likely to avoid touching water with their hands (using a ladle or tap to extract water from the storage vessel), and reported more frequent cleaning of vessels for fetching and storing water. However, these DiD estimates were substantively small and statistically insignificant; the evidence overall, therefore, points to households reacting to the testing intervention by spending cash rather than time or personal effort.

Difference in water handling and hygiene behaviors between tested and control households at baseline and follow-up

Perhaps as intriguing as these differences was the consistent and strong pattern of decay in averting behaviors over time. Table 5 illustrates the between-wave trends in both treatment and control groups. It reveals a distinct pattern of decreased self-reported use of recommended risk reduction behavior between the two waves of the survey. However, the covering of drinking water storage vessels with a tight screw cap, a practice that was confirmed by enumerators and not dependent on self-reports, did not decay in the same way. This behavior increased by 2% (or a factor of 0.2) between survey waves among the treatment group (significant at 10% confidence), but it did not change between the waves for the control group. Although DiD is not statistically significant, as shown in Table 4 , the difference in means at follow-up (a less conservative measure of the treatment effect) is significant. This pattern would be consistent with treatment households spending cash on new vessels on learning that their water is contaminated, whereas control households simply continued using the vessels that they had.

Differential trends in water handling and hygiene behaviors between tested and control households

This table represents an alternative presentation of the DiD values reported in Table 4; results come from the same regressions as those results reported in Table 4. All coefficients and 95% CI limits (shown in parentheses) are multiplied by 100, and therefore, they represent marginal effects in percentage point terms.

Overall, analysis of the differences between treatment and control households over time in this study revealed that people receiving water tests increased their purchase of drinking water from commercial sources by a factor of 1.5 compared with controls (95% CI = 1.21–1.75; P < 0.1%). More generally, there were large declines in reported protective behaviors over the 1 month between field visits, particularly among controls.

Commercial water is affordable but not negligibly costly by local standards—1 week's supply for the average household costs about 16 rupees or one-half of a day's wages for an average worker in these communities. However, more households on average were willing to incur these costs when they saw evidence that they were drinking contaminated water, and they were more willing to incur these costs than to undertake cash-cheaper but more time-intensive behaviors like cleaning their vessels more frequently.

Diarrheal disease remains a major source of preventable morbidity and mortality. 16 , 17 Many have asserted that effective interventions could use social marketing strategies that focus on information about water quality to promote preventive behaviors. 3 , 8 , 18 Because microbial contamination is impossible to detect with the naked eye, the link from water to disease may not be salient enough to affect behavior. Information specifically tailored to individual households—like a direct test for contamination of a household's own water supply—may be striking in a way that general social marketing messages are not. This result points to the importance of imperfect or incomplete information as one explanation for the persistence of diarrheal disease in these communities.

It would be premature to say that the impact of information on water, sanitation, and hygiene behaviors is significant or long lasting. It would certainly be useful to build on studies such as this one with development of procedures for tracking households' water-related behaviors and the consequences of those behaviors for the quality of consumed water that are perhaps less subject to potential self-reporting biases (e.g., including non-intrusive observation of behaviors or water quality testing at follow-up). In particular, it is difficult to know whether declines in self-reported measures of protective behaviors across the entire sample were the result of seasonal adjustments or some other factors. 19 Our DiD approach is likely, however, to sweep out biases arising from misclassification in the self-reports. In addition, our study does not provide data on the extent to which behavior change led to measurable improvements in water quality, which others have shown to be more difficult. 11 Nonetheless, those groups working to improve health by increased investments in preventive behavior should not overlook the impact that personally tailored information can have, at least in the short term. These results also suggest that the impact of information interventions is likely to interact with subsidies for the purchase of risk reduction technologies like commercially purified water.

Supplementary Material

Acknowledgments.

The authors thank Christine Poulos for help with setting up the study and the staff at GfK Mode for the instrumental role that they played in the execution of the fieldwork.

Financial support: Funding for the data collection was provided by the Acumen Fund, a nonprofit organization that “believes in using entrepreneurial approaches to solve the problems of global poverty.” It was conducted with the knowledge and moral support of a private sector commercial water provider; however, that firm provided no funding and played no role in the study design, data collection, or evaluation of results.

Authors' addresses: Amar Hamoudi, Marc Jeuland, and Subhrendu Pattanayak, Sanford School of Public Policy, Duke University, Durham, NC, E-mails: [email protected] , [email protected] , and [email protected] . Sarah Lombardo, Duke Global Health Institute, Duke University, Durham, NC, E-mail: moc.liamg@38odrab . Sumeet Patil, NEERMAN, Mumbai, India, E-mail: moc.namreen@litaprs . Shailesh Rai, J–PAL South Asia, New Delhi, India, E-mail: [email protected] .

• Open Access
• Published: 21 January 2016

Drinking water quality assessment and its effects on residents health in Wondo genet campus, Ethiopia

• Yirdaw Meride 1 &
• Bamlaku Ayenew 1  

Environmental Systems Research volume  5 , Article number:  1 ( 2016 ) Cite this article

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Metrics details

Water is a vital resource for human survival. Safe drinking water is a basic need for good health, and it is also a basic right of humans. The aim of this study was to analysis drinking water quality and its effect on communities residents of Wondo Genet.

The mean turbidity value obtained for Wondo Genet Campus is (0.98 NTU), and the average temperature was approximately 28.49 °C. The mean total dissolved solids concentration was found to be 118.19 mg/l, and EC value in Wondo Genet Campus was 192.14 μS/cm. The chloride mean value of this drinking water was 53.7 mg/l, and concentration of sulfate mean value was 0.33 mg/l. In the study areas magnesium ranges from 10.42–17.05 mg/l and the mean value of magnesium in water is 13.67 mg/l. The concentration of calcium ranges from 2.16–7.31 mg/l with an average value of 5.0 mg/l. In study areas, an average value of sodium was 31.23 mg/1and potassium is with an average value of 23.14 mg/1. Water samples collected from Wondo Genet Campus were analyzed for total coliform bacteria and ranged from 1 to 4/100 ml with an average value of 0.78 colony/100 ml.

On the basis of findings, it was concluded that drinking water of the study areas was that all physico–chemical parameters. All the Campus drinking water sampling sites were consistent with World Health Organization standard for drinking water (WHO).

Safe drinking water is a basic need for good health, and it is also a basic right of humans. Fresh water is already a limiting resource in many parts of the world. In the next century, it will become even more limiting due to increased population, urbanization, and climate change (Jackson et al. 2001 ).

Drinking water quality is a relative term that relates the composition of water with effects of natural processes and human activities. Deterioration of drinking water quality arises from introduction of chemical compounds into the water supply system through leaks and cross connection (Napacho and Manyele 2010 ).

Access to safe drinking water and sanitation is a global concern. However, developing countries, like Ethiopia, have suffered from a lack of access to safe drinking water from improved sources and to adequate sanitation services (WHO 2006 ). As a result, people are still dependent on unprotected water sources such as rivers, streams, springs and hand dug wells. Since these sources are open, they are highly susceptible to flood and birds, animals and human contamination (Messeret 2012 ).

The quality of water is affected by an increase in anthropogenic activities and any pollution either physical or chemical causes changes to the quality of the receiving water body (Aremu et al. 2011 ). Chemical contaminants occur in drinking water throughout the world which could possibly threaten human health. In addition, most sources are found near gullies where open field defecation is common and flood-washed wastes affect the quality of water (Messeret 2012 ).

The World Health Organization estimated that up to 80 % of all sicknesses and diseases in the world are caused by inadequate sanitation, polluted water or unavailability of water (WHO 1997 ). A review of 28 studies carried out by the World Bank gives the evidence that incidence of certain water borne, water washed, and water based and water sanitation associated diseases are related to the quality and quantity of water and sanitation available to users (Abebe 1986 ).

In Ethiopia over 60 % of the communicable diseases are due to poor environmental health conditions arising from unsafe and inadequate water supply and poor hygienic and sanitation practices (MOH 2011 ). About 80 % of the rural and 20 % of urban population have no access to safe water. Three-fourth of the health problems of children in the country are communicable diseases arising from the environment, specially water and sanitation. Forty-six percent of less than 5 years mortality is due to diarrhea in which water related diseases occupy a high proportion. The Ministry of Health, Ethiopia estimated 6000 children die each day from diarrhea and dehydration (MOH 2011 ).

There is no study that was conducted to prove the quality water in Wondo Genet Campus. Therefore, this study is conducted at Wondo Genet Campus to check drinking water quality and to suggest appropriate water treated mechanism.

Results and discussions

The turbidity of water depends on the quantity of solid matter present in the suspended state. It is a measure of light emitting properties of water and the test is used to indicate the quality of waste discharge with respect to colloidal matter. The mean turbidity value obtained for Wondo Genet Campus (0.98 NTU) is lower than the WHO recommended value of 5.00 NTU.

Temperature

The average temperature of water samples of the study area was 28.49 °C and in the range of 28–29 °C. Temperature in this study was found within permissible limit of WHO (30 °C). Ezeribe et al. ( 2012 ) reports similar result (29 °C) of well water in Nigeria.

Total dissolved solids (TDS)

Water has the ability to dissolve a wide range of inorganic and some organic minerals or salts such as potassium, calcium, sodium, bicarbonates, chlorides, magnesium, sulfates etc. These minerals produced un-wanted taste and diluted color in appearance of water. This is the important parameter for the use of water. The water with high TDS value indicates that water is highly mineralized. Desirable limit for TDS is 500 mg/l and maximum limit is 1000 mg/l which prescribed for drinking purpose. The concentration of TDS in present study was observed in the range of 114.7 and 121.2 mg/l. The mean total dissolved solids concentration in Wondo Genet campus was found to be 118.19 mg/l, and it is within the limit of WHO standards. Similar value was reported by Soylak et al. ( 2001 ), drinking water of turkey. High values of TDS in ground water are generally not harmful to human beings, but high concentration of these may affect persons who are suffering from kidney and heart diseases. Water containing high solid may cause laxative or constipation effects. According to Sasikaran et al. ( 2012 ).

Electrical conductivity (EC)

Pure water is not a good conductor of electric current rather’s a good insulator. Increase in ions concentration enhances the electrical conductivity of water. Generally, the amount of dissolved solids in water determines the electrical conductivity. Electrical conductivity (EC) actually measures the ionic process of a solution that enables it to transmit current. According to WHO standards, EC value should not exceeded 400 μS/cm. The current investigation indicated that EC value was 179.3–20 μS/cm with an average value of 192.14 μS/cm. Similar value was reported by Soylak et al. ( 2001 ) drinking water of turkey. These results clearly indicate that water in the study area was not considerably ionized and has the lower level of ionic concentration activity due to small dissolve solids (Table 1 ).

PH of water

PH is an important parameter in evaluating the acid–base balance of water. It is also the indicator of acidic or alkaline condition of water status. WHO has recommended maximum permissible limit of pH from 6.5 to 8.5. The current investigation ranges were 6.52–6.83 which are in the range of WHO standards. The overall result indicates that the Wondo Genet College water source is within the desirable and suitable range. Basically, the pH is determined by the amount of dissolved carbon dioxide (CO 2 ), which forms carbonic acid in water. Present investigation was similar with reports made by other researchers’ study (Edimeh et al. 2011 ; Aremu et al. 2011 ).

Chloride (Cl)

Chloride is mainly obtained from the dissolution of salts of hydrochloric acid as table salt (NaCl), NaCO 2 and added through industrial waste, sewage, sea water etc. Surface water bodies often have low concentration of chlorides as compare to ground water. It has key importance for metabolism activity in human body and other main physiological processes. High chloride concentration damages metallic pipes and structure, as well as harms growing plants. According to WHO standards, concentration of chloride should not exceed 250 mg/l. In the study areas, the chloride value ranges from 3–4.4 mg/l in Wondo Genet Campus, and the mean value of this drinking water was 3.7 mg/l. Similar value was reported by Soylak et al. ( 2001 ) drinking water of Turkey.

Sulfate mainly is derived from the dissolution of salts of sulfuric acid and abundantly found in almost all water bodies. High concentration of sulfate may be due to oxidation of pyrite and mine drainage etc. Sulfate concentration in natural water ranges from a few to a several 100 mg/liter, but no major negative impact of sulfate on human health is reported. The WHO has established 250 mg/l as the highest desirable limit of sulfate in drinking water. In study area, concentration of sulfate ranges from 0–3 mg/l in Wondo Genet Campus, and the mean value of SO 4 was 0.33 mg/l. The results exhibit that concentration of sulfate in Wondo Genet campus was lower than the standard limit and it may not be harmful for human health.

Magnesium (Mg)

Magnesium is the 8th most abundant element on earth crust and natural constituent of water. It is an essential for proper functioning of living organisms and found in minerals like dolomite, magnetite etc. Human body contains about 25 g of magnesium (60 % in bones and 40 % in muscles and tissues). According to WHO standards, the permissible range of magnesium in water should be 50 mg/l. In the study areas magnesium was ranges from 10.42 to 17.05 mg/l in Wondo Genet Campus and the mean value of magnesium in water is 13.67 mg/l. Similar value was reported by Soylak et al. ( 2001 ) drinking water of Turkey. The results exhibit that concentration of magnesium in Wondo Genet College was lower than the standard limit of WHO.

Calcium (Ca)

Calcium is 5th most abundant element on the earth crust and is very important for human cell physiology and bones. About 95 % of calcium in human body stored in bones and teeth. The high deficiency of calcium in humans may caused rickets, poor blood clotting, bones fracture etc. and the exceeding limit of calcium produced cardiovascular diseases. According to WHO ( 2011 ) standards, its permissible range in drinking water is 75 mg/l. In the study areas, results show that the concentration of calcium ranges from 2.16 to 7.31 mg/l in Wondo Genet campus with an average value of 5.08 mg/l.

Sodium (Na)

Sodium is a silver white metallic element and found in less quantity in water. Proper quantity of sodium in human body prevents many fatal diseases like kidney damages, hypertension, headache etc. In most of the countries, majority of water supply bears less than 20 mg/l, while in some countries the sodium quantity in water exceeded from 250 mg/l (WHO 1984 ). According to WHO standards, concentration of sodium in drinking water is 200 mg/1. In the study areas, the finding shows that sodium concentration ranges from 28.54 to 34.19 mg/1 at Wondo Genet campus with an average value of 31.23.

Potassium (k)

Potassium is silver white alkali which is highly reactive with water. Potassium is necessary for living organism functioning hence found in all human and animal tissues particularly in plants cells. The total potassium amount in human body lies between 110 and 140 g. It is vital for human body functions like heart protection, regulation of blood pressure, protein dissolution, muscle contraction, nerve stimulus etc. Potassium is deficient in rare but may led to depression, muscle weakness, heart rhythm disorder etc. According to WHO standards the permissible limit of potassium is 12 mg/1. Results show that the concentration of potassium in study areas ranges from 20.83 to 27.51 mg/1. Wondo Genet College with an average value of 23.14 mg/1. Present investigation was similar with reports made by other researchers’ study (Edimeh et al. 2011 ; Aremu et al. 2011 ). These results did not meet the WHO standards and may become diseases associated from potassium extreme surpassed.

Nitrate (NO 3 )

Nitrate one of the most important diseases causing parameters of water quality particularly blue baby syndrome in infants. The sources of nitrate are nitrogen cycle, industrial waste, nitrogenous fertilizers etc. The WHO allows maximum permissible limit of nitrate 5 mg/l in drinking water. In study areas, results more clear that the concentration of nitrate ranges from 1.42 to 4.97 mg/l in Wondo Genet campus with an average value of 2.67 mg/l. These results indicate that the quantity of nitrate in the study site is acceptable in Wondo Genet campus (Table 2 ).

Bacterial contamination

The total coliform group has been selected as the primary indicator bacteria for the presence of disease causing organisms in drinking water. It is a primary indicator of suitability of water for consumption. If large numbers of coliforms are found in water, there is a high probability that other pathogenic bacteria or organisms exist. The WHO and Ethiopian drinking water guidelines require the absence of total coliform in public drinking water supplies.

In this study, all sampling sites were not detected of faecal coliform bacteria. Figure  1 shows the mean values of total coliform bacteria in drinking water collected from the study area. All drinking water samples collected from Wondo Genet Campus were analyzed for total coliform bacteria and ranged from 1 to 4/100 ml with an average value of 0.78 colony/100 ml. In Wondo Genet College, the starting point of drinking water sources (Dam1), the second (Dam2) and Dam3 samples showed the presence of total coliform bacteria (Fig.  1 ). According to WHO ( 2011 ) risk associated in Wondo Genet campus drinking water is low risk (1–10 count/100 ml).

The mean values of total coliform bacteria in drinking water

According to the study all water sampling sites in Wondo Genet campus were meet world health organization standards and Ethiopia drinking water guideline. Figure  2 indicated that mean value of the study sites were under the limit of WHO standards.

Comparison of water quality parameters of drinking water of Wondo Genet campus with WHO and Ethiopia standards

Effect of water quality for residence health’s

Diseases related to contamination of drinking-water constitute a major burden on human health. Interventions to improve the quality of drinking-water provide significant benefits to health. Water is essential to sustain life, and a satisfactory (adequate, safe and accessible) supply must be available to all (Ayenew 2004 ).

Improving access to safe drinking-water can result in tangible benefits to health. Every effort should be made to achieve a drinking-water quality as safe as practicable. The great majority of evident water-related health problems are the result of microbial (bacteriological, viral, protozoan or other biological) contamination (Ayenew 2004 ).

Excessive amount of physical, chemical and biological parameters accumulated in drinking water sources, leads to affect human health. As discussed in the result, all Wondo Genet drinking water sources are under limit of WHO and Ethiopian guideline standards. Therefore, the present study was found the drinking water safe and no residence health impacts.

On the basis of findings, it was concluded that drinking water of the study areas was that all physico–chemical parameters in all the College drinking water sampling sites, and they were consistent with World Health Organization standard for drinking water (WHO). The samples were analyzed for intended water quality parameters following internationally recognized and well established analytical techniques.

It is evident that all the values of sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), chloride (Cl), SO 4 , and NO 3 fall under the permissible limit and there were no toxicity problem. Water samples showed no extreme variations in the concentrations of cations and anions. In addition, bacteriological determination of water from College drinking water sources was carried out to be sure if the water was safe for drinking and other domestic application. The study revealed that all the College water sampling sites were not contained fecal coliforms except the three water sampling sites had total coliforms.

The study was conducted in Wondo Genet College of Forestry and Natural Resources campus, which is located in north eastern direction from the town of Hawassa and about 263 km south of Addis Ababa (Fig.  3 ). It lies between 38°37′ and 38°42′ East longitude and 7°02′ and 7°07′ north latitude. Landscape of the study area varies with an altitude ranging between 1600 and 2580 meters above sea level. Landscape of the study area varies with an altitude ranging between 1600 and 2580 meters above sea level.

Map of study area

The study area is categorized under Dega (cold) agro-ecological zone at the upper part and Woina Dega (temperate) agro-ecological zone at the lower part of the area. The rainfall distribution of the study area is bi-modal, where short rain falls during spring and the major rain comes in summer and stays for the first two months of the autumn season. The annual temperature and rainfall range from 17 to 19 °C and from 700 to 1400 mm, respectively (Wondo Genet office of Agriculture 2011).

Methodology

Water samples were taken at ten locations of Wondo Genet campus drinking water sources. Three water samples were taken at each water caching locations. Ten (10) water samples were collected from different locations of the Wondo Genet campus. Sampling sites for water were selected purposely which represents the entire water bodies.

Instead of this study small dam indicates the starting point of Wondo Genet campus drinking water sources rather than large dams constructed for other purpose. Taps were operated or run for at least 5 min prior to sampling to ensure collection of a representative sample (temperature and electrical conductivity were monitored to verify this). Each sample’s physico–chemical properties of water were measured in the field using portable meters (electrical conductivity, pH and temperature) at the time of sampling. Water samples were placed in clean containers provided by the analytical laboratory (glass and acid-washed polyethylene for heavy metals) and immediately placed on ice. Nitric acid was used to preserve samples for metals analysis.

Analysis of water samples

Determination of ph.

The pH of the water samples was determined using the Hanna microprocessor pH meter. It was standardized with a buffer solution of pH range between 4 and 9.

Measurement of temperature

This was carried out at the site of sample collection using a mobile thermometer. This was done by dipping the thermometer into the sample and recording the stable reading.

Determination of conductivity

This was done using a Jenway conductivity meter. The probe was dipped into the container of the samples until a stable reading will be obtained and recorded.

Determination of total dissolved solids (TDS)

This was measured using Gravimetric Method: A portion of water was filtered out and 10 ml of the filtrate measured into a pre-weighed evaporating dish. Filtrate water samples were dried in an oven at a temperature of 103 to 105 °C for \(2\frac{1}{2}\)  h. The dish was transferred into a desiccators and allowed cool to room temperature and were weighed.

In this formula, A stands for the weight of the evaporating dish + filtrate, and B stands for the weight of the evaporating dish on its own Mahmud et al. ( 2014 ).

Chemical analysis

Chloride concentration was determined using titrimetric methods. The chloride content was determined by argentometric method. The samples were titrated with standard silver nitrate using potassium chromate indicator. Calcium ions concentrations were determined using EDTA titrimetric method. Sulphate ions concentration was determined using colorimetric method.

Microorganism analysis

In the membrane filtration method, a 100 ml water sample was vacuumed through a filter using a small hand pump. After filtration, the bacteria remain on the filter paper was placed in a Petri dish with a nutrient solution (also known as culture media, broth or agar). The Petri dishes were placed in an incubator at a specific temperature and time which can vary according the type of indicator bacteria and culture media (e.g. total coliforms were incubated at 35 °C and fecal coliforms were incubated at 44.5 °C with some types of culture media). After incubation, the bacteria colonies were seen with the naked eye or using a magnifying glass. The size and color of the colonies depends on the type of bacteria and culture media were used.

Statically analysis

All data generated was analyzed statistically by calculating the mean and compare the mean value with the acceptable standards. Data collected was statistically analyzed using Statistical Package for Social Sciences (SPSS 20).

Abbreviations

ethylene dinitrilo tetra acetic acid

Minstor of Health

nephelometric turbidity units

total dissolved solid

World Health Organization

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Authors’ contributions

YM: participated in designing the research idea, field data collection, data analysis, interpretation and report writing; BA: participated in field data collection, interpretation and report writing. Both authors read and approved the final manuscript.

Authors’ information

Yirdaw Meride: Lecturer at Hawassa University, Wondo Genet College of Forestry and Natural Resources. He teaches and undertakes research on solid waste, carbon sequestration and water quality. He has published three articles mainly in international journals. Bamlaku Ayenew: Lecturer at Hawassa University, Wondo Genet College of Forestry and Natural Resources. He teaches and undertakes research on Natural Resource Economics. He has published three article with previous author and other colleagues.

Acknowledgements

Hawassa University, Wondo Genet College of Forestry and Natural Resources provided financial support for field data collection and water laboratory analysis. The authors thank anonymous reviewers for constructive comments.

Competing interests

The authors declare that they have no competing interests.

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Meride, Y., Ayenew, B. Drinking water quality assessment and its effects on residents health in Wondo genet campus, Ethiopia. Environ Syst Res 5 , 1 (2016). https://doi.org/10.1186/s40068-016-0053-6

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• Published: 11 April 2022

Water quality assessment and evaluation of human health risk of drinking water from source to point of use at Thulamela municipality, Limpopo Province

• N. Luvhimbi 1 ,
• T. G. Tshitangano 1 ,
• J. T. Mabunda 1 ,
• F. C. Olaniyi 1 &
• J. N. Edokpayi 2  

Scientific Reports volume  12 , Article number:  6059 ( 2022 ) Cite this article

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• Environmental sciences
• Risk factors

Water quality has been linked to health outcomes across the world. This study evaluated the physico-chemical and bacteriological quality of drinking water supplied by the municipality from source to the point of use at Thulamela municipality, Limpopo Province, South Africa; assessed the community practices regarding collection and storage of water and determined the human health risks associated with consumption of the water. Assessment of water quality was carried out on 114 samples. Questionnaires were used to determine the community’s practices of water transportation from source to the point-of-use and storage activities. Many of the households reported constant water supply interruptions and the majority (92.2%) do not treat their water before use. While E. coli and total coliform were not detected in the water samples at source (dam), most of the samples from the street taps and at the point of use (household storage containers) were found to be contaminated with high levels of E. coli and total coliform. The levels of E. coli and total coliform detected during the wet season were higher than the levels detected during the dry season. Trace metals’ levels in the drinking water samples were within permissible range of both the South African National Standards and World Health Organisation. The calculated non-carcinogenic effects using hazard quotient toxicity potential and cumulative hazard index of drinking water through ingestion and dermal pathways were less than unity, implying that consumption of the water could pose no significant non-carcinogenic health risk. Intermittent interruption in municipal water supply and certain water transportation and storage practices by community members increase the risk of water contamination. We recommend a more consistent supply of treated municipal water in Limpopo province and training of residents on hygienic practices of transportation and storage of drinking water from the source to the point of use.

Introduction

Water is among the major essential resources for the sustenance of humans, agriculture and industry. Social and economic progress are based and sustained upon this pre-eminent resource 1 . Availability and easy access to safe and quality water is a fundamental human right 2 and availability of clean water and sanitation for all has been listed as one of the goals to be achieved by the year 2030 for sustainable development by the United Nations General Assembly (UNGA) 3 .

The physical, chemical, biological and aesthetic properties of water are the parameters used to describe its quality and determine its capability for a variety of uses including the protection of human health and the aquatic ecosystem. Most of these properties are influenced by constituents that are either dissolved or suspended in water and water quality can be influenced by both natural processes and human activities 4 , 5 . The capacity of a population to safeguard sustainable access to adequate quantities and acceptable quality of water for sustaining livelihoods of human well-being and socioeconomic growth; as well as ensuring protection against pollution and water related disasters; and for conserving ecosystems in a climate of peace and political balance is regarded to as water security 6 .

Although the world’s multitudes have access to water, in numerous places, the available water is seldom safe for human drinking and not obtainable in sufficient quantities to meet basic health needs 7 . The World Health Organization (WHO) estimated that about 1.1 billion people globally drink unsafe water and most diarrheal diseases in the world (88%) is attributed to unsafe water, poor sanitation and unhygienic practices. In addition, the water supply sector is facing enormous challenges due to climate change, global warming and urbanization. Insufficient quantity and poor quality of water have serious impact on sustainable development, especially in developing countries 8 .

The quality of water supplied by the municipality is to be measured against the national standards for drinking water developed by the federal governments and other relevant bodies 9 . These standards considered some attributes to be of primary importance to the quality of drinking water, while others are considered to be of secondary importance. Generally, the guidelines for drinking water quality recommend that faecal indicator bacteria (FIB), especially Escherichia coli ( E. coli ) or thermo tolerant coliform (TTC), should not be found in any 100 mL of drinking water sample 8 .

Despite the availability of these standards and guidelines, numerous WHO and United Nations International Children Emergency Fund (UNICEF) reports have documented faecal contamination of drinking water sources, including enhanced sources of drinking water like the pipe water, especially in low-income countries 10 . Water-related diseases remain the primary cause of a high mortality rate for children under the age of five years worldwide. These problems are specifically seen in rural areas of developing countries. In addition, emerging contaminants and disinfection by-products have been associated with chronic health problems for people in both developed and developing countries 11 . Efforts by governmental and non-governmental organizations to ensure water security and safety in recent years have failed in many areas due to a lack of sustainability of water supply infrastructures 12 .

Water quality, especially regarding the microbiological content, can be compromised during collection, transport, and home storage. Possible sources of drinking water contamination are open field defecation, animal wastes, economic activities (agricultural, industrial and businesses), wastes from residential areas as well as flooding. Any water source, especially is vulnerable to such contamination 13 . Thus, access to a safe source alone does not ensure the quality of water that is consumed, and a good water source alone does not automatically translate to full health benefits in the absence of improved water storage and sanitation 14 . In developing countries, it has been observed that drinking-water frequently becomes re-contaminated following its collection and during storage in homes 15 .

Previous studies in developing countries have identified a progressive contamination of drinking water samples with E. coli and total coliforms from source to the point of use in the households, especially as a result of using dirty containers for collection and storage processes 16 , 17 , 18 . Also, the type of water treatment method employed at household levels, the type of container used to store drinking water, the number of days of water storage, inadequate knowledge and a lack of personal and domestic hygiene have all been linked with levels of water contamination in households 19 , 20 .

In South Africa, many communities have access to treated water supplied by the government. However, the water is more likely to be piped into individual households in the urban than rural areas. In many rural communities, the water is provided through the street taps and residents have to collect from those taps and transport the water to their households. Also, water supply interruptions are frequently experienced in rural communities, hence, the need for long-term water storage. A previous study of water quality in South Africa reported better quality of water at source than the water samples obtained from the household storage containers, showing that water could be contaminated in the process of transporting it from source to the point of use 21 .

This study was conducted in a rural community at Thulamela Municipality, Limpopo province, South Africa, to describe the community’s drinking water handling practices from source to the point of use in the households and evaluate the quality of the water from source (the reservoir), main distribution systems (street taps), yard connections (household taps) and at the point of use (household storage containers). Water quality assessment was done by assessing the microbial contamination and trace metal concentrations, and the possible health risks due to exposure of humans to the harmful pathogens and trace metals in the drinking water were determined.

The study was conducted at Lufule village in Thulamela municipality, Limpopo Province, South Africa. The municipality is situated in the eastern subtropical region of the province. The province is generally hot and humid and it receives much of its rainfall during summer (October–March) 22 . Lufule village is made up of 386 households and a total population of 1, 617 residents 23 . The study area includes Nandoni Dam (main reservoir) which acquires its raw water from Luvuvhu river that flows through Mutoti and Ha-Budeli villages just a few kilometers away from Thohoyandou town. Nandoni dam is where purification process takes place to ensure that the water meets the standards set for drinking water. This dam is the main source of water around the municipality, and it is the one which supplies water to selected areas around the dam, including Lufule village. Water samples for analysis were collected from the dam (D), street taps (ST), household taps (HT) and household storage containers (HSC) (Fig.  1 ).

Map of the study area showing water samples’ collection areas.

Research design

This study adopted a quantitative design comprising of field survey and water analysis.

Field survey

The survey was done to identify the selected households and their shared source of drinking water (street taps). The village was divided into 10 quadrants for sampling purposes. From each quadrant, 6 households were randomly selected where questionnaires were distributed and household water samples were also collected for analysis.

Quantitative data collection

A structured interviewer-administered questionnaire was employed for data collection in the selected households. The population of Lufule village residents aged 15–69 years is 1, 026 (Census, 2011). About 10% of the adult population (~ 103) was selected to complete the questionnaires to represent the entire population. However, a total of 120 questionnaires were distributed, to take care of those which might be lacking vital information and therefore would not qualify to be analysed. Adults between the ages of 18 and 69 years were randomly selected to complete the questionnaire which includes questions concerning demographic and socio-economic statuses of the respondents, water use practices, sanitation, hygiene practices as well as perception of water quality and health. The face validity of the instrument was ensured by experts in the Department of Public Health, University of Venda, who reviewed questionnaire and confirmed that the items measure the concepts of interest relevant to the study 24 . Respondents were given time to go through the questionnaire and the researcher was present to clear any misunderstanding that may arise.

Water sampling

Permission to collect water samples from the reservoir tank at the Nandoni water treatment plant and households was obtained from the plant manager and the households’ heads respectively. Two sampling sites were identified at the dam, from where a water sample each was collected during the dry and the wet season. Similarly, 8 sampling sites were identified from the street and household taps, while 60 sampling sites were targeted for the household storage containers. However, only 39 household sites were accessible for sample collection, due to unavailability of the residents at the times of the researcher’s visit. Thus, water samples were collected from a total of 57 sites. Samples were collected from each of the sites during the dry (12th–20th April, 2019) and wet seasons (9th–12th December, 2019) between the hours of 08h00 and 14h30. A total of 114 samples were collected during the sampling period: 4 from the reservoir, 16 from street taps, 16 from household taps and 78 from households’ storage systems. Water samples were collected in 500 mL sterile polyethylene bottles. After collection, the containers were transported to the laboratory on ice in a cooler box. Each of the samples was tested for physico-chemical parameters, microbial parameters and trace metals’ concentration.

Physicochemical parameters’ analysis

Onsite analysis of temperature, pH, Electrical conductivity (EC) and Total Dissolved Solids (TDS) were performed immediately after sampling using a multimeter (model HI “HANNA” instruments), following the standards protocols and methods of American Public Health Association (APHA) 25 . The instrument was calibrated in accordance with the manufacturer’s guideline before taking the measurements. The value of each sample was taken after submerging the probe in the water and held for a couple of minutes to achieve a reliable reading. After measurement of each sample, the probe was rinsed with de-ionized water to avoid cross contamination among different samples.

ICP-OES and ICP-MS analyses of major and trace elements

An inductively coupled plasma optical emission spectrophotometer (ICP-OES) was used to analyse the major metals (Calcium (Ca), Sodium (Na), Potassium (K) and Magnesium (Mg)) in the water samples while inductively coupled plasma mass spectrophotometer (ICP-MS) was used to analyze the trace metals. The instrument was standardized with a multi-element calibration standard IV for ICP for Copper (Cu), Manganese (Mn), Iron (Fe), Chromium (Cr), Cadmium (Cd), Arsenic (As), Nickel (Ni), Zinc (Zn), Lead (Pb) and Cobalt (Co) and analytical precision was checked by frequently analysing the standards as well as blanks. ICP multi Standard solution of 1000 ppm for K, Ca, Mg and Na was prepared with NH 4 OAC for analysis to verify the accuracy of the calibration of the instrument and quantification of selected metals before sample analysis, as well as throughout the analysis to monitor drift.

Microbiological water quality analysis

Analysis of microbial parameters was conducted within 6 h of collection as recommended by APHA 25 . Viable Total coliform and E. coli were quantified in each sample using the IDEXX technique approved by the United States Environmental Protection Agency (USEPA). Colilert media was added to 100 mL sample and mixed until dissolved completely. The solution was poured into an IDEXX Quanti-Tray/2000 and sealed using the Quanti-Tray sealer 26 . The samples were incubated at 35 °C for 24 h. Trays were scanned using a fluorescent UV lamp to count fluorescent wells positive for E. coli concentration and counted with the most probable number (MPN) table provided by the manufacturer 27 .

Health risk assessment

Risk assessment have been estimated for ingestion and dermal pathways. Exposure pathway to water for ingestion and dermal routes are calculated using Eqs. ( 1 ) and ( 2 ) below:

where Exp ing : exposure dose through ingestion of water (mg/kg/day); BW: average body weight (70 kg for adults; 15 kg for children); Exp derm : exposure dose through dermal absorption (mg/kg/day); C water : average concentration of the estimated metals in water (μg/L); IR: ingestion rate in this study (2.0 L/day for adults; 1.0 L/day for children); ED: exposure duration (70 years for adults; and 6 years for children);AT: averaging time (25,550 days for an adult; 2190 days for a child); EF: exposure frequency (365 days/year) SA: exposed skin area (18.000 cm 2 for adults; 6600 cm 2 for children); K p : dermal permeability coefficient in water, (cm/h), 0.001 for Cu, Mn, Fe and Cd, while 0.0006 for Zn; 0.002 for Cr and 0.004 for Pb; ET: exposure time (0.58 h/ day for adults; 1 h/day for children) and CF: unit conversion factor (0.001 L/cm 3 ) 28 .

The hazard quotient (HQ) of non-carcinogenic risk by ingestion pathway can be determined by Eq. ( 3 )

where RfD ing is ingestion toxicity reference dose (mg/kg/day). An HQ under 1 is assumed to be safe and taken as significant non-carcinogenic, but HQ value above 1 may indicate a major potential health concern associated with over-exposure of humans to the contaminants 28 .

The total non-carcinogenic risk is represented by hazard index (HI). HI < 1 means the non-carcinogenic risk is acceptable, while HI > 1 indicates the risk is beyond the acceptable level 29 . The HI of a given pollutant through multiple pathways can be calculated by summing the hazard quotients by Eq. ( 4 ) below.

Carcinogenic risks for ingestion pathway is calculated by Eq. ( 5 ). For the selected metals in the study, carcinogenic risk (CR ing ) can be defined as the probability that an individual will develop cancer during his lifetime due to exposure under specific scenarios 30 .

where CRing is carcinogenic risk via ingestion route and SF ing is the carcinogenic slope factor.

Data analysis

Data obtained from the survey were analysed using Microsoft Excel and presented as descriptive statistics in the form of tables and graphs. The experimental data obtained was compared with the South African National Standards (SANS) 31 and Department of Water Affairs and Forestry (DWAF) 32 guidelines for domestic water use.

Ethics approval and consent to participate

The ethical clearance for this study was granted by the University of Venda Health, Safety and Research Ethics’ Committee (SHS/19/PH/14/1104). Permission to conduct the study was obtained from the Department of Water affairs, Limpopo province, Vhembe district Municipality and the selected households. Respondents were duly informed about the study and informed consent was obtained from all of them. The basic ethical principles of voluntary participation, informed consent, anonymity and confidentiality of respondents were duly complied with during data collection, analysis and reporting.

Consent for publication

Not applicable.

Socio-demographic characteristics of respondents

A total of 120 questionnaires were distributed but only 115 were completed, making a good response rate of 95%. The socio-demographic characteristics of the respondents are presented in Table 1 .

Household water supply

Many households (68.7%) had their primary water source from the municipality piped into their yards, but only 5.2% have the water flowing within their houses. The others have to fetch water at their neighbours’ yards or use the public taps on the streets. When the primary water supply is interrupted (i.e. when there is no water flowing through the pipes within the houses, yards or the public taps due to water rationing activities by the municipality, leakage of water distribution pipes, vandalization of pipes during road maintenance, etc.), the interruption usually lasts between a week or two, during which the respondents resort to other alternative sources. A return trip to the secondary source of water usually takes between 10 and 30 min for more than half of the respondents (53.0%) (Table 2 ).

Water storage and treatment practices at the household

Household water was most frequently stored in plastic buckets (n = 78, 67.8%), but ceramic vessels, metal buckets and other containers are also used for water storage (Fig.  2 ). Most households reported that their drinking water containers were covered (n = 111, 96.5%). More than half (53.9%) of the respondents used cups with handles to collect water from the storage containers whereas 37.4% used cups with no handles. Only 7.8% households reported that they treat their water before use mainly by boiling. Approximately 82.6% of respondent are of the opinion that one cannot get sick from drinking water and only 17.4% knew the risks that come with untreated water, and cited diarrhoea, schistosomiasis, cholera, fever, vomiting, ear infections, malnutrition, rash, flu and malaria as specific illnesses associated with water. Despite these perceptions, the majority (76.5%) were satisfied with their current water source. The few (23.5%) who were not satisfied cited poor quality, uncleanness, cloudiness, bad odour and taste in the water as reasons for their dissatisfaction (Table 3 ).

Examples of household water storage containers, some with lids and others without lids (photo from fieldwork).

Sanitation practices at the household level

More than half of the respondents (67%) use pit toilets, whereas only 26.1% use the flush to septic tank system, most of the toilets (93.9%) have a concrete floor. About 76.5% of households do not have designated place to wash their hands, however, all respondents indicated that they always wash their hands with soap or any of its other alternatives before preparing meals and after using the toilet (Table 4 ).

Water samples analysis

The water samples analyses comprise of microbial analysis, physico-chemical analysis and trace metals' parameters.

Microbial analysis

The samples from the reservoir during dry and wet season had 0 MPN/100 mL of total coliform and E. coli and were within the recommended limits of WHO and SANS for drinking water. During the wet season, seven out of the eight water samples collected from the street taps were contaminated with total coliform, while four of the samples taken from the same source were contaminated with total coliform during the dry season. Water samples from street taps 3 and 7 (ST 3 and ST7) were contaminated with total coliform during both seasons, however, the total coliform counts during the wet season were more than the counts during the dry season. None of the samples was contaminated with E. coli during the dry season, however, 2 samples from the street taps (ST3 & ST6) were found to be contaminated with E. coli during the wet season. Samples from household taps showed a similar trend with the street taps—with all samples being contaminated with total coliform during the wet season. Though 7 of the 8 samples taken from the household taps were contaminated with total coliform during the dry season, the samples from the same sources showed a higher level of total coliform in the wet season, with almost all the samples showing contamination at maximum detection levels of more than 2000 MPN/100 mL, except one sample (HT8) which showed a higher level of contamination with total coliform during the dry compared with the wet season. Only one sample (HT4) was found to be contaminated with E. coli during both dry and wet season. This shows that total coliform contamination levels are higher during the wet season than the dry season (Table 5 ).

Water samples from household storage containers (HSC) showed a higher level of total coliform during the wet season than the dry season and more samples were contaminated with E. coli during the wet season also (Table 6 ). A higher level of contamination was recorded for the HSCs compared to the street and household taps.

Physico-chemical analysis

In the reservoir samples, the pH value ranged from 8.37 to 8.45, EC ranged between 183 and 259 µS/cm whereas TDS varied between 118 and 168 mg/L. Similarly, in the street tap samples, pH value ranged from 7.28 and 9.33, EC ranged between 26 and 867 µS/cm whereas TDS varied between 16 and 562 mg/L (Fig.  3 ).

EC and TDS levels for the street taps and reservoir samples.

In the household taps, pH value ranged from 7.70–9.98, EC range between 28–895 µS/cm and TDS varied between 18 and 572 mg/L (Fig.  4 ).

EC and TDS levels for household taps.

In household storage container samples, the pH value ranges from 7.67–9.77, EC ranged between 19–903 µS/cm and TDS values ranged from 12–1148 mg/L (Fig.  5 ).

EC and TDS levels for household storage container samples.

Analysis of cations and trace metals in water

To detect the cations’ and trace metals’ concentrations in the water samples, representative samples from each of the sources were selected for analysis. The concentration of Calcium ranged between 2.14 and 31.65 mg/L, Potassium concentration ranged from 0.14 to 1.85 mg/L, Magnesium concentration varied from 1.32 to 16.59 mg/L, Sodium ranged from 0.18 to 12.96 mg/L (Table 7 ).

Trace metals’ analysis

The minimum and maximum concentrations of trace metals (Al, Mn, Fe, Co, Ni, Cu, Zn, As and Pb) present in water samples from selected street taps, household taps and household storage containers are presented in Table 8 .

Hazard quotient (HQ) and carcinogenic risk assessment

Table 9 presents the exposure dosage and hazard quotient (HQ) for ingestion and dermal pathway for metals. The HQ ing and HQ derm for all analyzed trace metals in both children and adults were less than one unit, indicating that there are no potential non-carcinogenic health risks associated with consumption of the water. Table 10 presents the total Hazard Quotient and Health risk index (HI) for trace metals in the water samples, showing that residents of the study area are not susceptible to non-cancer risks due to exposure to trace metals in drinking water. Table 11 presents the cancer risk associated with the levels of Ni, As and Pb in the drinking water samples. The table shows that only the maximum levels of lead had the highest chance of cancer risks for both adults and children.

This study provides information about the quality of drinking water in a selected rural community of Thulamela municipality of Limpopo province, South Africa, taking into consideration the physicochemical, microbiological and trace metals’ parameters of the treated water supplied to the village by the government, through the municipality. Many participants in the study have their primary source of water piped into their yards, while very few have water in their houses. This implies that getting water for household use would involve collecting the water from the yard and then into the storage containers. Those who do not have the taps in their yards have to collect water from the neighbours’ yards or the street taps. This observation is not restricted to the study area, as a similar situation has been observed in other rural communities of Limpopo Province 21 . This need to pass water through multiple containers before the point of use increases the risk of contamination.

Residents of the study area, just like residents of other settlements in Thulamela Municipality 21 , store their drinking water in plastic buckets, ceramic vessels, jerry cans and other containers. Almost all the respondents (96.5%) claim that their water storage vessels are covered and that their drinking water usually stays for less than a week in the storage containers (87.8%). Covering of water storage containers reduces the risk of water contamination from dust or other airborne particles. However, intermittent interruption of municipal water supply lasting for a week or more in the study area and the consequent use of alternative sources of water predispose the residents to various health risks as intermittent interruption in water supply has been linked to higher chances of contamination in the distribution systems, compared with continuous supply; in addition, the alternative sources of water may not be of a good quality as the treated municipal water 33 , 34 , yet, more than half of the respondents in this study (53%) use water directly from source without any form of treatment. This is because many residents in rural communities of Limpopo province believe that the water they drink is of good quality and thus do not need any further treatment 21 . The few who treat their water before drinking mostly use the boiling method. While boiling and other home-based interventions like solar disinfection of water have been reported to improve the quality of drinking water; drinking vessels, like cups, have also been implicated in water re-contamination of treated water at the point of use 16 and most respondents (91.3%) in this study admittedly use cups to collect water from the storage containers. The risk of contamination is even increased when cups without handles are used, where there is a higher chance that the water collector would touch the water in the container with his/her fingers. The Centres for Disease Control and Prevention (CDC) recommends that containers for drinking water should be fitted with a small opening with a cover or a spigot, through which water can be collected while the container remains closed, without dipping any potentially contaminated object into the container 35 . However, it is noteworthy that all the respondents claim to always wash their hands with soap (or its equivalents) and water after using the toilets, a constant practice of hand washing after using the toilet has been associated with a reduced risk of water contamination with E. coli 19 .

Treated water from the dam tested negative for both total coliform and E. coli hence complied with regulatory standards of SANS 31 and WHO 8 . The results could probably be due to the use of chlorine as a disinfectant in the treatment plant. Using disinfectants, pathogenic bacteria from the water can be killed and water made safe for the user. Similar studies have also reported that treated water in urban water treatment plants contains no total coliforms and E. coli 36 . In contrast, treated water sources in rural areas have been reported to have considerable levels of total coliform and E. coli 37 . The reason alluded to this include lack of disinfectant, no residual chlorine in the treated water, high prevalence of open defecation and unhygienic practices in proximity to water sources 38 .

From the water samples collected from the street taps, 62.5% were found to be contaminated with total coliform during the dry season, while the percentage rose to 87.5% during the wet season. The street tap which is about 13 km from the reservoir recorded high levels of total coliform ranging from 1.0 -2000 MPN/100 mL with most of the sites exceeding the WHO guidelines of 10 MPN/100 mL 8 . In both seasons, all the samples tested negative for E. coli , this complies with the WHO guideline of 0 MPN/100 mL. While the water leaving the treatment plant met bacteriological standards, the detection of coliform bacteria in the distribution lines suggest that the water is contaminated in the distribution networks. This could be due to the adherence of bacteria onto biofilms or accidental point source contamination by broken pipes, installation and repair works 39 . Furthermore, the water samples from households’ storage containers were contaminated by total coliform (73% and 85%) and E. coli (10.4% and 13.2%) during the dry and wet season, respectively. Microbiological contamination of household water stored in containers could be due to unhygienic practices occurring between the collection point and the point-of-use 40 , 41 .

Generally, higher levels of contamination were recorded in the wet season than in the dry season. The wet season in Thulamela Municipality is often characterized with increased temperature which could lead to favourable condition for microbial growth. Also, the treatment plant usually makes use of the same amount of chlorine for water purification during both seasons, even though influent water would be of a higher turbidity during the wet season, hence reducing the levels of residual chlorine 42 .

The pH of the analyzed samples from the study area ranged from 7.15 to 9.92. Most of the samples were within the values recommended by SANS (5 to 9.7) and comparable to results from previous similar studies 31 , 43 . Also, the electrical conductivity of all water samples from this study ranged from 28 µS/cm to 903 µS/cm which complied with the recommended value of SANS: < 1700 µS/cm 31 . The presence of dissolved solids such as calcium, chloride, and magnesium in water samples is responsible for its electrical conductivity 44 .

Total dissolved solids are the inorganic salts and small amounts of organic substance, which are present as solution in water 45 . Water has the ability to dissolve a wide range of inorganic and some organic minerals or salts such as potassium, calcium, sodium, bicarbonates, chlorides, magnesium, sulphates, etc. These minerals produced unwanted taste and colour in water 46 . A high TDS value indicates that water is highly mineralised. The recommended TDS value set for drinking water quality is ≤ 1200 mg/L 31 . In this study, the TDS values ranged from 18 mg/L to 572 mg/L. Hence, the TDS of all the household’s storage samples complied with the guidelines and consistent with previous studies 47 .

The analysis of magnesium (1.32 to 16.59 mg/L) and calcium (2.14 to 31.65 mg/L) concentrations showed that they were within the permissible range recommended for drinking water by SANS 31 and WHO 8 . All living organisms depend on magnesium in all types of cells, body tissues and organs for variety of functions while calcium is very important for human cell physiology and bones. Similar studies in Ethiopia and Turkey also showed acceptable levels of these metals in drinking water 46 , 48 . Likewise, the levels of potassium (0.14 to 1.85 mg/L) and sodium (0.18 to 12.96 mg/L) were within the permissible limit of WHO and SANS and may not cause health related problems. Sodium is essential in humans for the regulation of body fluid and electrolytes, and for proper functioning of the nerves and muscles, however, excessive sodium in the body can increase the risk of developing a high blood pressure, cardiovascular diseases and kidney damage 49 , 50 . Potassium is very important for protein synthesis and carbohydrate metabolism, thus, it is very important for normal growth and body building in humans, but, excessive quantity of potassium in the body (hyperkalemia) is characterized with irritability, decreased urine production and cardiac arrest 51 .

Metals like copper (Cu), cobalt (Co) and zinc (Zn) are essential requirements for normal body growth and functions of living organisms, however, in high concentrations, they are considered highly toxic for human and aquatic life 42 . Elevated trace metal(loids) concentrations could deteriorate water quality and pose significant health risks to the public due to their toxicity, persistence, and bio accumulative nature 52 . In this study, the concentrations of Manganese, Cobalt, Nickel and Copper all complied with the recommended concentration by SANS for domestic water use.

Aluminum concentration in the drinking water samples ranged from 1.25—13.46 µg/L. All analysed samples complied with the recommended concentration of ≤ 300 µg/L for domestic water use 31 . The recorded levels of Al in water from this study should not pose any health risk. At a high concentration, aluminium affects the nervous system, and it is linked to several diseases, such as Parkinson’s and Alzheimer’s diseases 53 . Iron (Fe) is an essential element for human health, required for the production of protein haemoglobin, which carries oxygen from our lungs to the other parts of the body. Insufficient or excess levels of iron can have negative effect on body functions 54 . The recommended concentration of iron in drinking water is ≤ 2000 µg/L 31 . In this study, the concentration of iron in the samples ranged from 0.96 to 73.53 µg/L. Similar results were reported by Jamshaid et al. in Khyber Pakhtunkhwa province 55 . A high concentration of Fe in water can give water a metallic taste, even though it is still safe to drink 56 .

The levels of Pb, As and Zn were in the range of 0.02–0.57 µg/L, 0.02–0.17 µg/L, and 2.54–194.96 µg/L, respectively whereas Cr was not detected in the samples collected. The levels recorded complied with the SANS 31 and WHO 8 guidelines for drinking water. Similar results were reported by Mohod and Dhote 57 . Lead is not desirable in drinking water because it is carcinogenic and can cause growth impairment in children 41 . Inorganic arsenic is a confirmed carcinogen and is the most significant chemical contaminant in drinking-water globally 44 . Zinc deficiency can cause loss of appetite, decreased sense of taste and smell, slow wound healing and skin sores 58 . Cr is desirable at low concentration but can be harmful if present in elevated levels.

The hazard quotient (HQ) takes into consideration the oral toxicity reference dose for a trace metal that humans can be exposed to 59 . Health related risk associated with the exposure through ingestion depends on the weight, age and volume of water consumed by an individual. HQ ing and HQ derm for all analyzed trace metals in both children and adults were less than one unit (Table 9 ), indicating that there are no potential non-carcinogenic health risks associated with the consumption of the water from the study area either by children or adults. The calculated average cumulative health risk index (HI) for children and adult was 3.88E-02 and 1.78E-02, respectively. HQ across metals serve as a conservative assessment tool to estimate high-end risk rather than low end-risk in order to protect the public. This served as a screen value to determine whether there is major significant health risk 60 . The results in this study signifies that the population of the investigated area are not susceptible to non-cancer risks due to exposure to trace metals in drinking water. Similar observation has been reported by Bamuwamye et al. after investigating human health risk assessment of trace metals in Kampala (Uganda) drinking water 61 . It should be noted that the hazard index values for children were higher than that of adult, suggesting that children were more susceptible to non-carcinogenic risk from the trace metals.

Drinking water with trace metals such as Pb, As, Cr and Cd could potentially enhance the risk of cancer in human beings 62 , 63 . Long term exposure to low amounts of toxic metals might, consequently, result in many types of cancers. Using As, Ni and Pb carcinogens, the total exposure risks of the residents in Table 11 . For trace metals, an acceptable carcinogenic risk value of less than 1 × 10 −6 is considered as insignificant and the cancer risk can be neglected; while an acceptable carcinogenic risk value of above 1 × 10 –4 is considered as harmful and the cancer risk is worrisome. Amongst the studied trace metals, only the maximum levels of lead for both adults and children had the highest chance of cancer risks (1.93E−03 and 4.46E−03) while Arsenic and Nickel have no chance of cancer risk with values of 3.34E−06; 7.72E−06 and 2.24E−05; 5.18E−05, in both adults and children respectively. The only cancer risk to residents of the studied area could be from the cumulative ingestion of lead in their drinking water. The levels of Pb recorded in this study complied to the SANS guideline value for safe drinking water. While the levels of Pb from the dam and the street pipes were relatively low, higher levels where recorded at household taps and storage containers and this may be due to the kind of storage containers and pipes used in those households. Generally, the water supply is of low Pb levels which should not pose any health risk to the consumers. However, the residents in rural areas should be properly educated on the kind of materials to be used for safe storage of water which should not pose an additional health burden. The likelihood of cancer risk was only associated with the consumption of the highest levels of Pb reported for a life time for adults (set at 70 years) and 6 years for children. Consistent consumption of water from the same source throughout an adult’s lifetime is unlikely as residents in those communities may change their locations at some points, hence reducing the possible risk associated with consistent exposure to the same levels of Pb.

Conclusions

The study shows that as distance increases from the treatment reservoir to distribution points, the cross-contamination rate also increases, therefore, good hygienic practices is required while transporting, storing and using water. Unhygienic handling practices at any point between collection and use contribute to the deterioration of drinking water quality.

The physicochemical, bacteriological quality and trace metals’ concentration of water samples from treated source, street taps and household storage containers were majorly within the permissible range of both WHO and SANS drinking water standards. HQ for both children and adults were less than unity, showing that the drinking water poses less significance health threat to both children and adults. Amongst the studied trace metals, only the maximum level of lead for both adults and children has the highest chance of cancer risks.

We recommend that appropriate measures should be taken to maintain residual free chlorine at the distribution points, supply of municipal treated water should be more consistent in all the rural communities of Thulamela municipality, Limpopo province and residents should be trained on hygienic practices of transportation and storage of drinking water from the source to the point of use.

Data availability

The datasets used and analysed during the current study are available from the first author on reasonable request.

Abbreviations

American Public Health Association

Centres for Disease Control and Prevention

Department of Water Affairs and Forestry

Electrical conductivity

Health risk index

Hazard quotient

Household storage containers

Household taps

Inductively coupled plasma mass spectrophotometer

Inductively coupled plasma optical emission spectrophotometer

Most probable number

South African National Standards

Street taps

Total Dissolved Solids

United Nations General Assembly

United Nations International Children Emergency Fund

United States Environmental Protection Agency

World Health Organization

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Acknowledgements

The authors wish to thank the University of Venda Health, Safety and Research Ethics’ Committee, the Department of Water affairs, Limpopo province and Vhembe district Municipality for granting the permission to conduct this study. We also thank all the respondents from the selected households in Lufule community.

The study was funded by the Research and Publication Committee of the University of Venda (Grant number: SHS/19/PH/14/1104).

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N. Luvhimbi, T. G. Tshitangano, J. T. Mabunda & F. C. Olaniyi

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L.N. and J.N.E. conceptualized the study, L.N. collected and analysed the data, T.G.T., J.T. M., and J.N.E. supervised the data collection and analysis. F.C.O. drafted the original manuscript, J.N.E. reviewed and edited the original manuscript. All authors approved the final manuscript.

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Luvhimbi, N., Tshitangano, T.G., Mabunda, J.T. et al. Water quality assessment and evaluation of human health risk of drinking water from source to point of use at Thulamela municipality, Limpopo Province. Sci Rep 12 , 6059 (2022). https://doi.org/10.1038/s41598-022-10092-4

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DOI : https://doi.org/10.1038/s41598-022-10092-4

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