hypothesis on drinking water

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Published: 07 August 2020

A randomized, double-blind water taste test to evaluate the equivalence of taste between tap water and filtered water in the Taipei metropolis

Jing-Rong Jhuang 1 ,
Wen-Chung Lee 1 , 2 &
Chang-Chuan Chan 2 , 3

Scientific Reports volume 10 , Article number: 13387 ( 2020 ) Cite this article

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Energy and society
Environmental social sciences
Psychology and behaviour
Sustainability

High water quality and sufficient water availability are the main concerns of water users. Promoting the efficient use of tap water can contribute to sustainable drinking water management and progress towards Sustainable Development Goals. In many metropolises, water suppliers treat municipal water with appropriate treatment processes and well-maintained distribution infrastructure. Under this circumstance, it is acceptable that municipal water can be a source of drinking water. The presence of residual chlorine in tap water, connected to municipal water supply, inactivates pathogenic microorganisms and prevents recontamination. However, adding chlorine to tap water may affect the organoleptic properties of drinking water. On the other hand, the use of point-of-use (POU) water dispensers, which provides an additional treatment step on tap water, is not energy-efficient. A randomized, double-blind water taste test was conducted in the Taipei metropolis to assess whether tap water from public drinking fountains and filtered water from POU water dispensers have similar organoleptic properties. An odds ratio (OR) and the area under the receiver operating characteristic curve (AUC) were used to measure the participants’ ability to distinguish between the two water varieties. A five-region hypothesis test was conducted to test the OR, and a 95% bootstrap confidence interval of the AUC was calculated. The results of the study showed that the 95% five-region confidence interval of OR equal to (0.5, 1.49), and the 95% bootstrap confidence interval of AUC equal to (0.42, 0.56). These results implied that people in the Taipei metropolis could not distinguish between tap water and filtered water. It is recommended that more drinking fountains be installed and maintained fully functional and clean to achieve excellence in tap water access.

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Introduction.

High water quality and sufficient water availability are the main concerns of water users. Water utilities must treat and supply water to meet specific water quality standards. In many metropolises, water suppliers treat municipal water with appropriate treatment processes and well-maintained distribution infrastructure, ensuring high-quality municipal water and sufficient water availability. Under this circumstance, it is acceptable that municipal water can be a source of drinking water. Tap water, connected to municipal water supply, is a common and efficient source of drinking water. The presence of residual chlorine in tap water inactivates pathogenic microorganisms that cause waterborne diseases 1 , 2 and prevents recontamination during storage or transportation 3 . The World Health Organization (WHO) provided guidelines for drinking-water quality that residual chlorine levels in tap water should be maintained at concentrations of 0.2–5 mg/L 4 .

The United Nations General Assembly has proposed Sustainable Development Goals (SDGs) to achieve a more sustainable future by 2030 5 . Among the 17 goals, SDG 6 addresses the availability and sustainable management of water and sanitation. Promoting the efficient use of tap water can contribute to sustainable drinking water management and progress towards SDG 6. However, adding chlorine to tap water exhibits effects on the taste and odor of drinking water, which can reduce people’s preference for tap water 6 , 7 , 8 and impede acceptance and sustainability of the water quality intervention 9 . The point-of-use (POU) water dispenser, which works by connecting to municipal water supply and drawing water from the waterline that is already in place, provides an additional treatment step on tap water. The application of replaceable filter in a POU water dispenser can improve the organoleptic quality of tap water 10 , 11 , 12 by removing chlorine, solid precipitates, discoloration, unpleasant scent. A POU water dispenser has the option to provide hot or cold water on command. And the predominant demand for energy in such water dispensing systems is from the heating or cooling of water before consumption. In Taiwan, the total energy consumed by 5.48 million water dispensers was 3.15 billion kWh per year 13 . The water dispenser was also the fifth electricity-consuming household appliances in Taiwan 14 . High energy consumption can complicate the achievement of SDG 7, which represents affordable and sustainable energy. Also, in a city, tap water and water from POU water dispensers are connected to the municipal water supply, from the same water source, water treatment processes, and distribution piping system. For sustainability in water supply, it is unnecessary to treat water that is already of good quality at the end-user point. Therefore, a better understanding of the public perception and preferences of tap water can contribute to improvements in water management, consumer services, and sustainability.

Municipal water in Taipei city meets drinking-water standards in WHO, USA, Europe, and Japan 15 . The perception and preferences of tap water are still unknown in the Taipei metropolis. The study aimed to investigate whether tap water has organoleptic properties similar to filtered water from POU water dispensers. It was expected that people could not distinguish the two water varieties such that there is no advantage in treating water that is already of good quality at the end-user point.

Material and methods

Study design and randomization.

A randomized, double-blind water taste test was designed (Fig. 1 ). Water from a public drinking fountain (tap water) and cold water from a POU water dispenser (filtered water) were obtained and were let stand for an hour at room temperature. A thermometer was used to ensure that the temperature was at 25 °C for both the water varieties. Paper cups with the same appearance were prepared. For each paper cup, a random decimal number between 0 and 1 was generated by using a computer, and the cup was assigned to the tap-water group if the number was ≥ 0.5 and to the filtered-water group if the number was < 0.5. A fixed and identical amount (200 ml) of the appropriate water variety was poured into each paper cup according to the group to which it was assigned. A sealed letter containing the group information was attached to the outside of each paper cup.

Procedure for the water taste test.

One-on-one interviews were conducted. The interviewer, who was not involved in water sample preparation, first told the participant that residual chlorine exists in tap water from public drinking fountains but not in filtered water from POU water dispensers. Next, the participant was invited to taste a cup of water. (Participants who refuse to drink the water were excluded.) Neither the interviewer nor the participant knew which water variety was served in the cup, except that it could be tap water or filtered water with equal probability. The interviewer then instructed the participant to guess the water variety. After the guess, the participant opened the sealed letter to reveal the correct answer.

Measures of distinguishability

The participants’ ability to distinguish between the two water varieties was measured using an odds ratio (OR) 16 as follows:

where Se (sensitivity) and Sp (specificity) represent the probabilities of guessing the correct answer in the tap-water group and the filtered-water group, respectively. When obtaining OR = 1, it indicated that the proportions of the participants guessing “tap water” were equal in the two groups; that is, the participants could not distinguish between the two water varieties by any means. When obtaining OR > 1, it indicated that the proportion of the participants replying “tap water” was higher in the tap-water group than in the filtered-water group. The higher the OR, the stronger the participants’ abilities to distinguish between the water varieties. When obtaining OR < 1, it indicated that the participants were not only unable to distinguish between the water varieties but also tended to guess incorrectly. The smaller the OR, the stronger the tendency to guess incorrectly.

The participants' ability to distinguish between the water samples was also measured using the area under the receiver operating characteristic curve (AUC) 17 :

An AUC of 0.5 indicated that the participants could not distinguish the two water varieties by any means. An AUC of > 0.5 indicated that the participants could distinguish between the water varieties, and the higher the value, the stronger was their ability to distinguish between the water varieties. An AUC of < 0.5 indicated that the participants could not distinguish between the water varieties, and the smaller the value, the stronger was the tendency to guess incorrectly.

Statistical analyses

A newly proposed five-region hypothesis test 18 was conducted to test the OR. The five regions were defined as $\hbox{OR}>2$ (a recognizable ability to distinguish between the water varieties; we also consider a more lenient criterion of $\hbox{OR}>1.5$ for this category), $1< \hbox{OR} \le 2$ (a negligible ability to distinguish between the water varieties; also a stricter criterion of $1<\hbox{OR} \le 1.5$ for this category), $\hbox{OR}=1$ (no ability to distinguish between the water varieties), $0.5\le \hbox{OR} <1$ (a weak tendency to guess incorrectly), and $\hbox{OR}<0.5$ (a strong tendency to guess incorrectly). The 95% five-region confidence interval 18 of the OR was also calculated. To conclude 18 that the participants have no recognizable ability to distinguish between the two water varieties ( $\hbox{OR}\le 2$ ), at least 207 participants were required to be recruited to achieve a power of 80% at a significance level of 0.05. Furthermore, we generated 10,000 bootstrap samples and calculated a 95% bootstrap confidence interval 19 of the AUC. All analyses were performed with R version 3.5.2 20 .

Consent for publication

Not applicable.

Ethical approval and consent to participate

Study site, participants, and data collection, water supply and sanitation.

There are two state-owned water utilities in Taiwan; Taiwan Water Corporation provides water supply to Taiwan except for the Taipei metropolis, whereas the Taipei Water Department is exclusively responsible for supplying water to the Taipei metropolis. The primary source of raw water is Xindian Creek, representing 97% of the total raw water supply in the Taipei metropolis. Qingtan Dam and Zhitan Dam are in operation at the Xindian Creek. The two water intake units take in 1.08 (Qingtan Dam) and 2.70 (Zhitan Dam) million cubic meters of raw water daily, respectively, which are conveyed with gravity via tunnels to the Zhangxingm, Gongguan, or Zhitan Purification Plants for treatment. The treatment process comprises testing, applying chemical disinfectants, coagulation, mixing, sedimentation, and filtering. Wastes discharged from the water purification process, including settled flocculating waste and filter backwash waste, are sent to Zhitan or Gongguan purification plants to process.

Water pipeline network with a caliber ranging from 75 to 3,400 mm that add up to a total length over 3,000 km has been placed in the Taipei metropolis. A water supply monitoring and control system was developed in 1991 for better control of pressure changes and leakage in the distribution system, flexible adjustment of water supplies, and early detection and prevention of accidents. Due to the requirement for adjusting the delivery of treated water to meet demand adequately, 92 distribution basins have been set up. Also, 60 pumping stations have been set up at appropriate locations to enable water supply to reach the farthest ends of the distribution piping system, particularly those at high altitudes.

Some measures have been implemented in the Taipei metropolis to meet the goal of sustainable water resources. Automatic Water Quality Monitoring System was established in 1985 to monitor the water quality in the raw water intakes, the treatment process at its purification plants, and the distribution system. To enhance water availability for drinking, approximately 280 public drinking fountains that provide clean and safe tap water have been installed 21 . Also, a QR code that provides water users with updated information about the quality of tap water (turbidity, pH, and residual chlorine) was equipped on each public drinking fountain.

Participants and data collection

The study protocol was approved by the College of Public Health, National Taiwan University (NTU), where the study was conducted (in the Zhongzheng District of the Taipei metropolis). All methods were carried out following the guidelines and regulations of NTU. Students and teaching faculty members of the College of Public Health, NTU, were recruited for the study. Informed consent was obtained from all the participants. The study period was from March to April 2018. The primary source of drinking water in this study site (NTU Public Health Building) is the POU water dispensers. Currently, a public drinking fountain has been set up, which can be another choice for the students and the teaching faculty members to drink. The participants were invited to attend the water taste test in a small room, and after the test, they can win a gift. Eight well-trained interviewers collected data from the participants. The collected variables include gender and position of each participant, whether or not he (or she) had drunk cold water from water dispensers in the previous month and had drunk water from drinking fountains before, the water variety he (or she) guessed, the actual water variety he (or she) drank, and his (or her) preference for tap water from drinking fountains.

A total of 278 participants took part in the test; 139 were randomly assigned to the tap-water group and the remaining to the filtered-water group. Table 1 presents the baseline characteristics of the participants. The two groups did not differ significantly in their characteristics. Table 2 presents the results of the water analysis of the two water varieties. The water qualities of the two water varieties were similar except for total residual chlorine and pH.

Table 3 presents the results of the water taste test. A total of 216 participants (77.7%) replied, “tap water.” The numbers of the participants who replied, “tap water,” were 106 (76.3%) and 110 (79.1%) in the tap-water group and the filtered-water group, respectively. The Se, Sp, and OR estimates were 0.76, 0.21, and 0.85, respectively. Table 4 presents the results of the analysis of the participants’ abilities to distinguish between the two water varieties. The 95% five-region confidence interval of the OR for all the participants was (0.5, 1.49), excluding $\hbox{OR}>2$ (and also $\hbox{OR}>1.5$ ) and $\hbox{OR}<0.5$ entirely; the p-value for the $\hbox{OR}>2$ hypothesis (a recognizable ability to distinguish between the water varieties) was 0.01 (0.02 for the $\hbox{OR}>1.5$ hypothesis), and the p-value for the $\hbox{OR}<0.5$ hypothesis (a strong tendency to guess incorrectly) was 0.03. These results indicated that the participants could not distinguish between the two water varieties and that the indistinguishability of the water varieties was statistically significant. Besides, the estimate of the AUC was 0.49, with a 95% bootstrap confidence interval of (0.42, 0.56), which encompassed the null value of 0.5.

A subgroup analysis (Table 4 ) was also performed. The value of $\hbox{OR}>2$ was rejected in male participants, female participants, students, and those who have not drunk cold water from water dispensers in the previous month. The values of $\hbox{OR}>2$ and $\hbox{OR}<0.5$ were rejected in those who have drunk cold water from water dispensers in the previous month and those who have not drunk water from drinking fountains before. However, because of the small sample size, the power was insufficient to reject $\hbox{OR}>2$ or $\hbox{OR}<0.5$ in the faculty members and those who have drunk water from drinking water fountains before. The 95% bootstrap confidence intervals of the AUC encompassed 0.5 in all subgroups.

A randomized, double-blind water taste test was performed, and the results showed that the participants could not distinguish between tap water and filtered water. The participants (after the water taste test) were asked whether they were willing to drink from drinking fountains if they could choose to drink from POU water dispensers. Most of the participants (252, 90.6%) provided affirmative responses. Based on these findings, in general, it is unnecessary to treat municipal water in the Taipei metropolis at the end-user point.

In the water taste test, the participants were being told from the outset that the water to be drunk had a 50:50 chance of being from a drinking fountain and a water dispenser. However, the participants had a biased belief that the water was more likely to be from a drinking fountain than a water dispenser (78:22), perhaps because they tend to associate the taste of water dispensers with cold or hot water rather than room temperature water as in this study. Nevertheless, the OR, the primary measure in the study, is impervious to such a bias. The study aimed to prove the equivalence of the two water varieties on taste. A conventional hypothesis test can only prove nonequivalence; we cannot conclude that the taste of the two water varieties is equivalent when the test result is nonsignificant. By contrast, the five-region hypothesis test we used in this study is a legitimate test to conclude that the OR significantly fell into a pre-specified equivalence region (from 0.5 to 2.0; or from 0.5 to 1.5) of the two water varieties, which indicated the taste of the water varieties is statistically equivalent 22 .

In a group interview, participants may discuss the water tastes; therefore, in this study, a one-on-one interview was adopted to avoid possible contamination biases. In this study, students or teaching faculty members who had been smoking or eating within one hour before the water taste test were not excluded. However, the randomization was conducted to control any possible bias this may induce. In most settings, we believed that people would drink water from an easily accessible source to quench their thirst but would not drink deliberately from two different sources at the same time merely to compare the tastes. Therefore, each participant tasted only one water variety, unlike other studies, which let each participant taste no less than two water varieties 23 , 24 . In general, information about the characteristics of water samples is not to be given to tasters in a sensory evaluation test. In this study, information about residual chlorine exists in tap water was told before the water taste test because most of the participants have not drunk water from drinking fountains before, and the preference for tap water in the study site was unknown before the study.

Information about the chemical quality of the two water varieties would be crucial to evaluate the study results. According to previous studies, the taste detection thresholds for residual chlorine has an extensive regional variation, from 0.17 to 0.71 mg/L 4 , 24 , 25 . The residual chlorine levels of tap water ranged from 0.27 to 0.39 mg/L during the study. However, the two water varieties were allowed to stand for an hour at room temperature before the water taste test (for ensuring proper control). This procedure may allow some residual chlorine in tap water to dissipate and may have rendered the two water varieties more challenging to distinguish. An extreme pH value on filtered water was observed on one particular day in the study period, which may also influence the study results. A previous study 26 indicated that it is difficult to discriminate the two water varieties when the difference in total dissolved solids (TDS) among the two is lower than 150 mg/L. In this study, there was a minor difference (about 10 mg/L) in TDS among the two water varieties during the study period. Additionally, minerals are correlated with the taste of water 27 but were not measured in this study.

Bottled water, which is also an alternative to tap water 6 , 7 , 27 , 28 , 29 , was not compared in this study because whether consumers could perceive the presence of residual chlorine in drinking water was mainly concerned. Water samples in the study were only collected from a POU water dispenser and a public drinking fountain. Further studies can be conducted to validate our findings in other locations in the Taipei metropolis (internal validation) or other cities having similar water sources, treatment processes, and distribution piping systems (external validation). The study results could not be generalized and extrapolated to other water varieties with medium or high TDS or to consumers who are more sensitive to the residual chlorine level, for example, French consumers 25 , bottled water drinkers 25 , or professional water sommeliers.

Although a POU water dispenser can provide clean and safe drinking water to meet SDG 6, high energy consumption constitutes obstacles in achieving SDG 7 (affordable and clean energy). This problem exhibits a trade-off between SDG 6 and SDG 7 30 , 31 . By contrast, drinking tap water improves energy efficiency. In locations where tap water has acceptable quality at the end-user point, it is recommended the use of tap water for drinking to achieve the synergistic development of SDG 6 and SDG 7 by providing clean water with affordable energy. To drink hot or cold water, using kettle heaters and refrigerators are more energy-efficient than using water dispensers; the average electricity consumption by kettle heaters (14.38 kWh per month per household 32 ) is lower than that by water dispensers (26.00 kWh per month per household 14 ), and refrigerators are already in use in many households in Taiwan.

Conclusion and perspectives

The study results concluded that people in the Taipei metropolis could not distinguish between tap water and filtered water. It is recommended that more drinking fountains be installed and maintained fully functional and clean 33 , 34 to achieve excellence in tap water access. POU water dispensers with functions of either heating or cooling water managed by the government can be uninstalled or replaced with drinking fountains. Public education toward more tap water use should be implemented. Furthermore, risk indices 35 for assessing the water supply systems should be determined to prevent substantial water quality deterioration. For achieving sustainable water management, we suggest using reclaimed water 36 , 37 , 38 to balance water supply and demand.

Data availability

Data collected from the water taste test and R code for statistical analysis are available at https://github.com/yoyo830303/water-analysis . The Taipei Water Department provided data about the water quality analyses of the two water varieties.

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Acknowledgments

We thank the reviewers for their feedback, which helped to improve the manuscript quality. We would like to acknowledge Hua-Shan Shi, Mei-Ku Chen, Jui-Min Hsia, Jing-Syuan Zeng, Wei-Cheng Tsai, Shih-Hsiang Liao, Ching-Hsiang Chang, Wan-Chu Lin and I-Hsin Chang for their assistance with collecting data. This study was supported by grants from the Ministry of Science and Technology in Taiwan (MOST 105-2314-B-002-049-MY3, MOST 104-2314-B-002-118-MY3, MOST 108-2314-B-002-127-MY3, and MOST 108-3017-F-002-001), and the Population Health Research Center from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan (NTU-109L900308). No additional external funding was received for this study. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Contributions

W.-C.L. and J.-R.J. designed the study. J.-R.J. prepared the photograph in Fig. 1 , collected the data, conducted the statistical analysis and drafted the paper. Wen-Chung Lee and C.-C.C. supervised the study and wrote the paper. W.-C.L. and C.-C.C. are the guarantors. The corresponding authors attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

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Jhuang, JR., Lee, WC. & Chan, CC. A randomized, double-blind water taste test to evaluate the equivalence of taste between tap water and filtered water in the Taipei metropolis. Sci Rep 10 , 13387 (2020). https://doi.org/10.1038/s41598-020-70272-y

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Received : 14 February 2020

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DOI : https://doi.org/10.1038/s41598-020-70272-y

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What do you want to find out about your study site’s water quality, how will I measure it and what are your predictions?

Check Your Thinking: Scenario: There is an abandoned mine dump within 5 meters of your study site stream. How might contaminants in the mine waste be impacting your stream? When would be the best time of year/day to collect water monitoring data that could help answer this question? What tests should you conduct?

Using your recorded observations and information compiled in the first step, the next step is to come up with a testable question. You can use the previously mentioned question (Based on what I know about the pH, DO, temperature and turbidity of my site, is the water of a good enough quality to support aquatic life?) as it relates to the limitations of the World Water Monitoring Day kit, or come up with one of your own.

What results do you predict? For example, your hypothesis may be “I believe the pH, DO, temperature and turbidity of the water at my study site are of good enough quality to support aquatic life because there are no visible impacts to water quality upstream or on the site.” Once you’ve formulated your question, begin planning the experiment or, in this case, the water monitoring you will conduct .

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The MSP project is funded by an ESEA, Title II Part B Mathematics and Science Partnership Grant through the Montana Office of Public Instruction. MSP was developed by the Clark Fork Watershed Education Program and faculty from Montana Tech of The University of Montana and Montana State University , with support from other Montana University System Faculty.

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Why is water important?

We're often told that we need to drink more water, but exactly why is water important?

Why do we need to drink water?

What happens if you don’t drink enough water, what effect does water have on the body, drinking enough water.

If you’ve been pondering the question ‘why is water important?’ rest assured, you’re not alone. While it probably won’t come as a surprise to hear that everyone needs to drink water to survive, most of us invest in one of the best water bottles and commit to guzzling down our daily water intake without really understanding what makes water so vital.

There are quite a few things that make water necessary to the human body, from cellular functions, to aiding digestion, and even improving concentration and exercise performance. You’ve probably even heard the recommendation to drink a certain amount of water every day (usually about 8 glasses or so), but where does that number come from? And what happens if you don’t drink enough?

This article will tackle everything and anything you would need to know about why water is important, including why we need to drink water, what happens when we don’t get enough and the effect water has on our body. Let’s dive in!

Knowing how to stay hydrated with water is super important. Why? Well, largely because the human body is about 60% water and because we are continuously losing water through urine, sweat and even just breathing, we need to ensure we’re replacing that fluid so that our cells, tissues and organs can all function optimally.

Water is a solvent, which means that other substances can dissolve in it, which allows for their transportation between cells in the body. Substances like glucose (the body’s preferred fuel source) and amino acids (the building blocks of protein) dissolve very effectively in water, and use water as a carrier for them throughout the body.

Water also carries vitamins and minerals to and from the cells, and is vital in removing waste products from individual cells, as shown by research in the Biochemical Journal . Further, water consumption ensures appropriate blood volume, viscosity, and circulation, which is vital for the proper function of all organs and tissues of the body, according to a paper in Nutrition Reviews .

Water is also vitally important for regulating body temperature. It has a great capacity to store heat, preventing large, rapid drops in internal temperature, and through sweating, water has arguably the most efficient avenue to lose heat when environmental temperature is higher than body temperature, as per an article in Military Medicine .

Finally, water is essential to form many bodily fluids: tears, saliva, sweat, urine, and blood, amongst others. Water is also a highly effective lubricant for joints helping to produce synovial fluid and cartilage, which help keep joints healthy through smooth movements. Water also helps with joint health by maintaining cells’ shapes, acting as a shock absorber during impacting activities like walking or running, which even protects the brain and spinal cord, according to a review article in Nature .

Not drinking enough water can lead to dehydration very quickly, and it’s more common than we think. According to a 2020 paper in StatPearls , between 28% and 75% of adults in the US are dehydrated at any given moment. This is

attributed to a number of factors, notably overconsumption of caffeinated drinks like coffee and soft drinks, which a 2018 study in Nutrients lists as common replacements for water that act as a diuretic that cause the body to lose even more water.

Even ‘mild’ dehydration (a loss of water corresponding to 1-2% of body weight) can lead to significant impairments in cognitive function, concentration, alertness, memory, physical performance, sport-specific skills, and physical endurance, according to research in Nutrition Reviews .

According to a study in the Journal of Applied Physiology , larger losses in water corresponding to 4% of body weight (which research still considers ‘mild’) can lead to poor cardiovascular function as blood plasma volume drops which causes an increase in heart rate and stroke volume (the amount of blood the heart perfuses per beat). Dehydration of this level can also cause decreases in skin blood flow and sweating, which leads to an increase in body temperature, which can complicate any heat-induced dehydration, as per another study from the Journal of Applied Physiology .

As you may be able to tell, drinking water will have more or less the opposite effect to not drinking water, for all the reasons outlined earlier in the article. In an ideal world, we would all stay hydrated by drinking water regularly, and so we may never notice the effect that drinking water has because we’d never be dehydrated. However, we know that not to be the case.

Given the host of cognitive problems that dehydration can have on the body, drinking water can often improve your ability to focus, concentrate, and retain information. A lot of people also ask the question ‘does drinking water help you to lose weight?’ and evidence suggests that it absolutely can. Not only that, it aids in digestion, due to its role in nutrient absorption, and creation of digestive fluids and enzymes like hydrochloric acid. Drinking water can also reduce joint pain or wear and tear, due to its role in joint cushioning and maintenance of synovial fluid and cartilage.

woman getting a glass of water from the tap

Clearly, drinking water is utterly vital for a whole host of reasons, and unfortunately, just drinking water when thirsty isn’t going to be enough. Thirst is only triggered when water losses correspond to 1-3% body weight, which is enough to lead to mental and physical impairments. Plus, the issue with only drinking when thirsty is that thirst can be quenched before proper hydration is achieved, according to Nature .

The U.S. National Academies of Sciences, Engineering, and Medicine recommend drinking 92 fluid ounces (11.5 cups) per day for women, and 124 fluid ounces (15.5 cups) of water per day for men. However, many factors can affect how much water someone needs to drink: warmer environments increase sweating and water loss, drinking caffeinated drinks leads to a diuretic affect, and when exercising, sweat and respiration-induced water losses can reach 65 fluid ounces per hour according to a paper in the Journal of the American College of Nutrition .

It’s important to adjust your water intake appropriately to get all of its benefits, and avoid the potential downfalls of dehydration. If you’re keen to find new and novel ways to increase your water intake, check out our guide to how to drink more water.

HÄUSSINGER, D. (1996). The role of cellular hydration in the regulation of cell function. Biochemical Journal, 313(3), 697–710. https://pubmed.ncbi.nlm.nih.gov/8611144/

Jéquier, E., & Constant, F. (2009). Water as an essential nutrient: the physiological basis of hydration. European Journal of Clinical Nutrition, 64(2), 115–123. https://www.nature.com/articles/ejcn2009111

José, G. A., Mora-Rodríguez, R., Below, P. R., & Coyle, E. F. (1997). Dehydration markedly impairs cardiovascular function in hyperthermic endurance athletes during exercise. Journal of Applied Physiology, 82(4), 1229–1236. https://pubmed.ncbi.nlm.nih.gov/9104860/

Montain, S. J., Latzka, W. A., & Sawka, M. N. (1999). Fluid Replacement Recommendations for Training in Hot Weather. Military Medicine, 164(7), 502–508. https://pubmed.ncbi.nlm.nih.gov/10414066/

Murray, B. (2007). Hydration and Physical Performance. Journal of the American College of Nutrition, 26(sup5), 542S-548S. https://pubmed.ncbi.nlm.nih.gov/17921463/

Nishiyasu, T. S., Shi, X. G., Mack, G. W., & Nadel, E. R. (1991). Effect of hypovolemia on forearm vascular resistance control during exercise in the heat. Journal of Applied Physiology, 71(4), 1382–1386. https://pubmed.ncbi.nlm.nih.gov/1757361/

Reyes, C., & Cornelis, M. (2018). Caffeine in the Diet: Country-Level Consumption and Guidelines. Nutrients, 10(11), 1772. https://pubmed.ncbi.nlm.nih.gov/30445721/

Ritz, P., & Berrut, G. (2005). The Importance of Good Hydration for Day-to-Day Health. Nutrition Reviews, 63, S6–S13. https://pubmed.ncbi.nlm.nih.gov/16028567/

Water: How much should you drink every day? (2020, October 14). Mayo Clinic. Retrieved April 14, 2022, from https://www.mayoclinic.org/healthy-lifestyle/nutrition-and-healthy-eating/in-depth/water/art-20044256?reDate=14042022

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Will McAuley is a London-based Personal Trainer and Nutrition Coach who’s writing has appeared in Men’s Fitness and GQ magazine, covering exercise, nutrition and health. He has a Master’s degree in Strength & Conditioning from Middlesex University in London, is a published scientific author in the Journal of Strength and Conditioning Research, and holds a Bachelor’s degree in Linguistics from Trinity College Dublin.

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Drinking lots of water may seem like a healthy habit – here’s when and why it can prove toxic

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In late 2023, actor Brooke Shields suffered a seizure after “flooding” her body with water. Shields became dangerously low on sodium while preparing for her show by drinking loads of water. “I flooded my system and I drowned myself,” she would later explain. “And if you don’t have enough sodium in your blood or urine or your body, you can have a seizure.”

Shields said she found herself walking around outside for “no reason at all”, wondering: “Why am I out here?”

Then I walk into the restaurant and go to the sommelier who had just taken an hour to watch my run through. That’s when everything went black. Then my hands drop to my side and I go headfirst into the wall.

Shields added that she was “frothing at the mouth, totally blue, trying to swallow my tongue”.

Like Shields, many people may be unaware of the dangers of drinking excessive amounts of water – especially because hydration is so often associated with health benefits. Models and celebrities often advocate drinking lots of water to help maintain clear, smooth skin. Some social media influencers have promoted drinking a gallon of water daily for weight loss.

But excessive water consumption can cause hyponatraemia – a potentially fatal condition of low sodium in the blood.

Worried about hydration levels? Check your urine

The body strictly regulates its water content to maintain the optimum level of total body water and “osmolality” – the concentration of dissolved particles in your blood. Osmolality increases when you are dehydrated and decreases when you have too much fluid in your blood.

Osmolality is monitored by osmoreceptors that regulate sodium and water balance in the hypothalamus – the part of the brain that controls numerous hormones. These osmoreceptors signal the release of antidiuretic hormone (ADH), which acts on blood vessels and the kidneys to control the amount of water and salt in the body.

In healthy people, the body releases ADH when osmolality becomes high. ADH tells the kidneys to reabsorb water, which makes urine more concentrated. The reabsorbed water dilutes the blood, bringing osmolality back to normal levels.

Low blood osmolality suppresses the release of ADH, reducing how much water the kidneys reabsorb. This dilutes your urine, which the body then passes to rid itself of the excess water.

Healthy urine should be clear and odourless. Darker, yellower urine with a noticeable odour can indicate dehydration – although medications and certain foods, including asparagus , can affect urine colour and odour, too.

How much is too much?

Adults should consume two-to-three litres per day , of which around 20% comes from food. However, we can lose up to ten litres of water through perspiration – so sweating during exercise or in hot weather increases the amount of water we need to replace through drinking.

Some medical conditions can cause overhydration. Approximately one in five schizophrenia patients drink water compulsively, a dangerous condition known as psychogenic polydipsia . One long-term study found that patients with psychogenic polydipsia have a “74% greater chance of dying before a non-polydipsic patient”.

In some cases , people with anorexia nervosa can also suffer from compulsive water drinking.

For those suffering from polydipsia, treatment is focused on medication to reduce the urge to drink , as well as increasing sodium levels . This should be done gradually to avoid causing myelinolysis – neurological damage caused by rapid changes in sodium levels in nerve cells.

In rare but often highly publicised cases such as that of Leah Betts in 1995, some users of the illegal drug MDMA (also known as ecstasy) have died after drinking copious amounts of water to rehydrate after dancing and sweating.

The drug increases body temperature , so users drink water to avoid overheating. Unfortunately, MDMA also triggers the unnecessary release of ADH , causing water retention. The body becomes unable to rid itself of excess water, which affects its electrolyte levels – causing cells to swell with water.

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3. Generate Hypotheses

Developing a hypothesis regarding the cause of the outbreak is often challenging and is a crucial step in the outbreak investigation.

Many pathogens that cause waterborne diseases can also be transmitted by contaminated food or by contact with an infected person or animal. When looking for the source of the illness, investigators first need to decide on the likely mode(s) of transmission. The identified pathogen, where ill persons live, or the age of the patients may suggest a particular mode of transmission and could help identify a specific source. Hypothesis generation should be considered an iterative process in which possible explanations are continually refined or refuted.

When exposure to water is suspected as the source of contamination, public health officials interview ill cases to determine water exposures in the days or weeks prior to onset of illness. These interviews are called “hypothesis-generating interviews.” Interviews can either use a standardized questionnaire (e.g., “shotgun” questionnaire), or they can be open-ended. Standardized interviews include a set of questions used by public health officials to interview ill people during outbreak investigations. Open-ended interviews are not standardized and do not provide concrete exposures for analysis. Interviews will focus on activities and experiences that occurred during the pathogen’s incubation period—the time it takes to get sick after exposure to the contaminated water. A table of common waterborne pathogens and their incubation period is listed in the Appendices .

Based on all the information gathered, the investigators make a hypothesis about the likely source of the outbreak. If they are not able to develop a hypothesis, investigators can return to intensive, open-ended interviews or utilize a different set of standardized questions to develop clues to the outbreak source. Clues to the outbreak source might come from ill persons with few exposure opportunities or from interviewing cohorts (e.g., family groups or sports teams) within the larger outbreak population.

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There are many options for what to drink , but water is the best choice for most people who have access to safe drinking water. It is calorie-free and as easy to find as the nearest tap.

Water helps to restore fluids lost through metabolism, breathing, sweating, and the removal of waste. It helps to keep you from overheating, lubricates the joints and tissues, maintains healthy skin, and is necessary for proper digestion. It’s the perfect zero-calorie beverage for quenching thirst and rehydrating your body.

How Much Water Do I Need?

Water is an essential nutrient at every age, so optimal hydration is a key component for good health. Water accounts for about 60% of an adult’s body weight. We drink fluids when we feel thirst, the major signal alerting us when our body runs low on water. We also customarily drink beverages with meals to help with digestion. But sometimes we drink not based on these factors but on how much we think we should be drinking. One of the most familiar sayings is to aim for “8 glasses a day,” but this may not be appropriate for every person.

General recommendations

The National Academy of Medicine suggests an adequate intake of daily fluids of about 13 cups and 9 cups for healthy men and women, respectively, with 1 cup equaling 8 ounces. [1] Higher amounts may be needed for those who are physically active or exposed to very warm climates. Lower amounts may be needed for those with smaller body sizes. It’s important to note that this amount is not a daily target, but a general guide. In the average person, drinking less will not necessarily compromise one’s health as each person’s exact fluid needs vary, even day-to-day.
Fever, exercise, exposure to extreme temperature climates (very hot or cold), and excessive loss of body fluids (such as with vomiting or diarrhea) will increase fluid needs.
The amount and color of urine can provide a rough estimate of adequate hydration. Generally the color of urine darkens the more concentrated it is (meaning that it contains less water). However, foods, medications, and vitamin supplements can also change urine color. [1] Smaller volumes of urine may indicate dehydration, especially if also darker in color.
Alcohol can suppress anti-diuretic hormone, a fluid-regulating hormone that signals the kidneys to reduce urination and reabsorb water back into the body. Without it, the body flushes out water more easily. Enjoying more than a couple of drinks within a short time can increase the risk of dehydration, especially if taken on an empty stomach. To prevent this, take alcohol with food and sips of water.
Although caffeine has long been thought to have a diuretic effect, potentially leading to dehydration, research does not fully support this. The data suggest that more than 180 mg of caffeine daily (about two cups of brewed coffee) may increase urination in the short-term in some people, but will not necessarily lead to dehydration. Therefore, caffeinated beverages including coffee and tea can contribute to total daily water intake. [1]

Keep in mind that about 20% of our total water intake comes not from beverages but from water-rich foods like lettuce, leafy greens, cucumbers, bell peppers, summer squash, celery, berries, and melons.

Aside from including water-rich foods, the following chart is a guide for daily water intake based on age group from the National Academy of Medicine:

Preventing Dehydration: Is Thirst Enough?

As we age, however, the body’s regulation of fluid intake and thirst decline. Research has shown that both of these factors are impaired in the elderly. A Cochrane review found that commonly used indicators of dehydration in older adults (e.g., urine color and volume, feeling thirsty) are not effective and should not be solely used. [3] Certain conditions that impair mental ability and cognition, such as a stroke or dementia, can also impair thirst. People may also voluntarily limit drinking due to incontinence or difficulty getting to a bathroom. In addition to these situations, research has found that athletes, people who are ill, and infants may not have an adequate sense of thirst to replete their fluid needs. [2] Even mild dehydration may produce negative symptoms, so people who cannot rely on thirst or other usual measures may wish to use other strategies. For example, aim to fill a 20-ounce water bottle four times daily and sip throughout the day, or drink a large glass of water with each meal and snack.

Symptoms of dehydration that may occur with as little as a 2% water deficit:

Confusion or short-term memory loss
Mood changes like increased irritability or depression

Dehydration can increase the risk of certain medical conditions:

Urinary tract infections
Kidney stones
Constipation

Like most trends of the moment, alkaline water has become popular through celebrity backing with claims ranging from weight loss to curing cancer. The theory behind alkaline water is the same as that touting the benefits of eating alkaline foods, which purportedly counterbalances the health detriments caused by eating acid-producing foods like meat, sugar, and some grains.

From a scale of 0-14, a higher pH number is alkaline; a lower pH is acidic. The body tightly regulates blood pH levels to about 7.4 because veering away from this number to either extreme can cause negative side effects and even be life-threatening. However, diet alone cannot cause these extremes; they most commonly occur with conditions like uncontrolled diabetes, kidney disease, chronic lung disease, or alcohol abuse.

Alkaline water has a higher pH of about 8-9 than tap water of about 7, due to a higher mineral or salt content. Some water sources can be naturally alkaline if the water picks up minerals as it passes over rocks. However, most commercial brands of alkaline water have been manufactured using an ionizer that reportedly separates out the alkaline components and filters out the acid components, raising the pH. Some people add an alkaline substance like baking soda to regular water.

Scientific evidence is not conclusive on the acid-alkaline theory, also called the acid-ash theory, stating that eating a high amount of certain foods can slightly lower the pH of blood especially in the absence of eating foods supporting a higher alkaline blood pH like fruits, vegetables, and legumes. Controlled clinical trials have not shown that diet alone can significantly change the blood pH of healthy people. Moreover, a direct connection of blood pH in the low-normal range and chronic disease in humans has not been established.

BOTTOM LINE: If the idea of alkaline water encourages you to drink more, then go for it! But it’s likely that drinking plain regular water will provide similar health benefits from simply being well-hydrated—improved energy, mood, and digestive health

Is It Possible To Drink Too Much Water?

There is no Tolerable Upper Intake Level for water because the body can usually excrete extra water through urine or sweat. However, a condition called water toxicity is possible in rare cases, in which a large amount of fluids is taken in a short amount of time, which is faster than the kidney’s ability to excrete it. This leads to a dangerous condition called hyponatremia in which blood levels of sodium fall too low as too much water is taken. The excess total body water dilutes blood sodium levels, which can cause symptoms like confusion, nausea, seizures, and muscle spasms. Hyponatremia is usually only seen in ill people whose kidneys are not functioning properly or under conditions of extreme heat stress or prolonged strenuous exercise where the body cannot excrete the extra water. Very physically active people such as triathletes and marathon runners are at risk for this condition as they tend to drink large amounts of water, while simultaneously losing sodium through their sweat. Women and children are also more susceptible to hyponatremia because of their smaller body size.

Fun Flavors For Water

Pitcher of water filled with orange slices and mint leaves

Infused water

Instead of purchasing expensive flavored waters in the grocery store, you can easily make your own at home. Try adding any of the following to a cold glass or pitcher of water:

Sliced citrus fruits or zest (lemon, lime, orange, grapefruit)
Crushed fresh mint
Peeled, sliced fresh ginger or sliced cucumber
Crushed berries

Sparkling water with a splash of juice

Sparkling juices may have as many calories as sugary soda. Instead, make your own sparkling juice at home with 12 ounces of sparkling water and just an ounce or two of juice. For additional flavor, add sliced citrus or fresh herbs like mint.

TIP: To reduce waste, reconsider relying on single-use plastic water bottles and purchase a colorful 20-32 ounce refillable water thermos that is easy to wash and tote with you during the day.

Are seltzers and other fizzy waters safe and healthy to drink?

BOTTOM LINE: Carbonated waters, if unsweetened, are safe to drink and a good beverage choice. They are not associated with health problems that are linked with sweetened, carbonated beverages like soda.

Harvard T.H. Chan School of Public Health is a member of the Nutrition and Obesity Policy Research and Evaluation Network’s (NOPREN) Drinking Water Working Group. A collaborative network of the Centers for Disease Control and Prevention, the NOPREN Drinking Water Working Group focuses on policies and economic issues regarding free and safe drinking water access in various settings by conducting research and evaluation to help identify, develop and implement drinking-water-related policies, programs, and practices. Visit the network’s website to access recent water research and evidence-based resources.
The Harvard Prevention Research Center on Nutrition and Physical Activity provides tools and resources for making clean, cold, free water more accessible in environments like schools and afterschool programs, as well as tips for making water more tasty and fun for kids.
The National Academy of Sciences. Dietary References Intakes for Water, Potassium, Sodium, Chloride, and Sulfate. https://www.nap.edu/read/10925/chapter/6#102 Accessed 8/5/2019.
Millard-Stafford M, Wendland DM, O’Dea NK, Norman TL. Thirst and hydration status in everyday life. Nutr Rev . 2012 Nov;70 Suppl 2:S147-51.
Hooper L, Abdelhamid A, Attreed NJ, Campbell WW, Channell AM, et al. Clinical symptoms, signs and tests for identification of impending and current water-loss dehydration in older people. Cochrane Database Syst Rev . 2015 Apr 30;(4):CD009647.

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Bottled Water: United States Consumers and Their Perceptions of Water Quality

1 Department of Sociology, Iowa State University, 103 East Hall, Ames, IA 50011, USA; E-Mail: ude.etatsai@notromwl

Lois Wright Morton

Robert l. mahler.

2 PSES Department, University of Idaho, P.O. Box 442339, Moscow, ID 83844, USA; E-Mail: ude.ohadiu@RELHAMB

Consumption of bottled water is increasing worldwide. Prior research shows many consumers believe bottled water is convenient and has better taste than tap water, despite reports of a number of water quality incidents with bottled water. The authors explore the demographic and social factors associated with bottled water users in the U.S. and the relationship between bottled water use and perceptions of the quality of local water supply. They find that U.S. consumers are more likely to report bottled water as their primary drinking water source when they perceive that drinking water is not safe. Furthermore, those who give lower ratings to the quality of their ground water are more likely to regularly purchase bottle water for drinking and use bottle water as their primary drinking water source.

1. Introduction

Consumption of bottled water is increasing by ten percent every year worldwide, with the fastest growth seen in the developing countries of Asia and South America [ 1 ]. The United States (U.S.) is the largest consumer market for bottled water in the world. The U.S. consumption of bottled water in 2008 was estimated to be 8.6 billion gallons, or 27.6 gallons per person [ 2 ]. Despite the common belief that bottled water is safer to drink and has better taste than tap water, scientific studies have shown that the belief is not necessarily true [ 3 , 4 ]. Research also shows that the sales and consumption of bottled water can have environmental and social impacts whose consequences are yet to be fully understood [ 5 – 7 ]. After years of substantial growth in sales, the U.S. bottled water market is recently slowing down. The current economic downturn may have played a part in the drop; however, environmental concern is also an important factor. Some research has found that environmental awareness campaigns may have curbed consumer demand [ 8 – 10 ].

Previous studies about bottled water have focused on its production, regulation, sales and consumption, and criticism and concerns. However, few researchers have examined the relationship between consumer use of bottled water and perceptions of drinking water quality. In this article, the authors explore the demographic and social factors associated with bottled water users in the U.S. and the relationship between bottled water use and perceptions of the quality of local water supply. A brief discussion of bottled water and tap water and bottled water consumers is used to develop several hypotheses. These hypotheses are tested using a national dataset representing twenty-one U.S. states. Results and discussion are followed by implications directed toward educators and public policy makers as they fund and develop programs that promote knowledge about health and local drinking water.

1.1. Bottled Water vs. Tap Water

Bottled water has been used in place of tap water for its convenience, better taste, and perceived purity [ 1 , 3 , 11 ]. Perceptions of bottled water being of higher quality, however, are challenged by the increasing number of water quality incidents with bottled water [ 12 ]. A study showed that only five percent of the bottled water purchased in Cleveland, Ohio had the required fluoride recommended by the state, whereas the sampled tap water 100% met this requirement [ 3 ]. The same experiment also conducted bacteria count on both bottled water and tap water samples. The result showed that all of the tap water samples had a bacterial content under 3 CFUs/mL (colony-forming unit, a measure of viable bacterial or fungal numbers) and the bottled water samples' bacterial content ranged from 0.01–4,900 CFUs/mL. Although most of the water bottle samples were under 1 CFU/mL, there were 15 water bottle samples containing 6–4,900 CFUs/mL [ 3 ]. Another study focusing on the temperature and duration of storage for bottle water found that the bacterial growth in bottled water was markedly higher than that in tap water, especially at higher temperatures [ 4 ].

Many scientific reports on bottled water urge increased public awareness and development of guidelines/regulations on the industry of bottled water [ 1 ]. Incidents with bottled water quality are largely reported as associated with lenient regulations on bottled water. Bottled water plants are subject to the U.S. Food and Drug Administration (FDA) monitoring and inspection. Despite specific inspection requirements, bottled water plants are given low priority for safety inspection compared with other food plants because of FDA’s staffing and financial constraints [ 13 ]. The “Nutrition Facts” label on bottled water usually shows only limited information about the water [ 1 ].

Despite the popularity of bottled water in the U.S., there are a number of environmental and social concerns. Plastic bottles are a waste problem adding to landfill overload when not recycled. Water bottling plants have impacts on local groundwater aquifers and streams [ 5 ]. Taking too much water can reduce or deplete groundwater reserves and reduce the flow of streams and lakes, causing stress on ecosystems. Although 75% of the world bottled water is produced and distributed on a regional scale, trading and transporting the other 25% bottled water also raises the concern for pollution and carbon dioxide emission [ 6 ]. The price of bottled water is on average 500 to 1,000 times higher than that of tap water [ 6 ], contributing to concern for affordable access to drinking water. Limited resource populations that use bottled water for drinking are least able to afford the high cost associated with bottled water [ 1 ]. Another issue associated with increased consumption of bottled water is that it can erode public tap water revenues and the capacity of governments to provide necessary improvements in basic water infrastructure [ 7 ].

1.2. Consumers of Bottled Water

Eighty-five million bottles of water are consumed in the United States every day and more than thirty billion bottles a year [ 14 ]. The adoption of a health preventive action like drinking bottled water is suggested to be influenced by perception of risk associated with drinking water [ 15 ]. The perception of risk is also thought to be closely related to the subjective assessment of drinking water quality [ 11 ]. This suggests that perceptions of drinking water safety and beliefs about the ground and surface water quality in a local area might be explanatory factors for a decision to select bottled water over tap water.

Another safety factor influencing consumer decision to select bottled water over tap water is the type of water supply system where the consumer lives. Small water systems (small town, tribal system, rural water district) [ 16 ] in the U.S. were found to have problems complying with federal/state quality standards. According to one study, due to inadequate funding and facilities, small water systems reportedly violated federal drinking water regulations more frequently than larger ones [ 11 ]. Although the number of public water consumers whose water does not meet current standards has decreased significantly over years, the task of water regulation is still challenging given both the financial limitations and increasing public concern about their drinking water [ 11 ].

Socio-economic status is also a factor affecting consumer decisions, particularly given the high cost associated with bottled water. Gender and education differences have been found to affect preference of bottled water over tap water because of their noted differences in perception of environmental risk [ 11 , 17 ].

Risk perception and preventive behaviors are the result of complicated social, cultural, and psychological factors as well as objective information [ 18 ]. This suggests that because of the differences in economic, social, and environmental contexts, residents of different regions might have different attitudes towards bottled water. In an earlier study, the findings showed that people in the Pacific region had more per capita consumption of bottled water than in other places of the U.S. [ 11 ]. In this article, the regional factor is examined and the popularity of bottled water is mapped across geographic regions.

2. Experimental Section

2.1. hypotheses.

Prior studies of bottled water consumption have identified a variety of explanatory factors for consumption behavior. However, these factors have not been considered together in one single model. For example, the regional differences found between the Pacific and the rest parts of the U.S. might be due to confounding factors such as differences in community size, local water quality problems, or water supply systems. Therefore, we propose to test these variables of interest simultaneously using a logistic regression. Hypotheses regarding use of bottled water are as follows:

H1: Perceptions of poorer groundwater and surface water quality represent higher risk in drinking water and therefore are hypothesized to be associated with higher likelihood of purchasing bottle water as a primary drinking source compared to those reporting perceptions of higher water quality. Related, perceptions that drinking water is not safe are associated with higher likelihood of purchasing bottled water for drinking as a primary water source.
H2: Based on the observations about small water supply systems, we hypothesize that small water supply (community well and rural district) users are more likely to use bottled water for drinking compared to public municipal water supply users. Community size is used as a control variable.
H3: Because of the environmental impact associated with bottled water, we test the association between environmental attitudes and bottled water use. The association between the two is hypothesized to be that the more pro-environmental views a person holds, the less likely the person frequently uses bottled water for drinking.
H4: We hypothesize a regional effect on the use of bottled water, although the specific pattern about such regional differences is not clear at this stage.

Other variables tested in the logistic model include age, education, and gender.

2.2. Methodology

Data used for this study were collected from a national stratified random sample mail survey about water issues conducted by Dr. Robert Mahler of University of Idaho. Our analysis used data from twenty-one states, which partially cover five out of the ten U.S. EPA water regions [ 19 ]. Data were collected 2004 through 2009 (region 8 and 9, 2004; region 7, 2006; region 6, 2008; and region 4, 2009). Sample sizes for each state were calculated based on the state population and targeted sampling error of four to six percent, with anticipation that the return rate would exceed fifty percent [ 20 ]. In each individual state, samples were either randomly selected from phone books or obtained from a professional social sciences survey company (Survey Sampling International, Norwich, Connecticut). The questionnaires were pilot tested, revised, and then mailed to sampled names and addresses. The final sample size was 5,823. Standard mail survey methods [ 21 ] were followed in all the regions and institutional review board (IRB) approval was obtained from University of Idaho Office of Research Assurance prior to the survey process. Response rates of each state ranged from 37% to 70%, with median return rates reaching the targeted 50%. The questionnaires, generally about 50 questions, varied in their content and wording due to the regions’ differing priorities. However, there were a number of core questions that all states asked. It is these questions in common that make up our data set. These core survey items asked about respondents’ perceptions of water quality, use of bottled water, water supply type, general environmental attitudes, and demographic information.

Two sources of drinking water questions were of interest in this study. The first one was “where do you primarily get your drinking water.” Possible responses to this question included: private supply (private well, river, pond, lake, etc. ), public municipal supply, small water supply systems (including rural water district and community well), and purchase bottled water. If respondents chose “purchase bottled water” for this question, they were identified as primary users of bottled water.

The second question asked if the respondent “often use bottled water for drinking purposes.” If respondents answered “yes” to this question, they were labeled as regular users of bottled water. The above two questions were not mutually exclusive, which means that a primary bottled water user may be a regular bottled water user.

First, we tested hypotheses one, three and four on the primary bottled water users using a logistic regression model. The independent variables used in this logistic regression were as follows:

Surface and ground water quality perceptions. Respondents were asked to rate the surface and ground water quality in their area. Responses were coded 1 = poor, 2 = fair, 3 = very good/excellent.

Drinking water safety. The original question asked if the respondents felt their home drinking water is safe to drink. Response options were 0 = no, and 1 = yes.

Environmental attitudes . Respondents were asked to indicate where they stand on environmental issues by placing a mark on a line with numbers 1 to 10, where 1 represented preference for total natural resource use and 10 represented preference for total environmental protection.

Community size. Community size was measured by asking respondents to choose from the options which best described their community size, although no strict definition was given to the term “community”. Community sizes were measured with five categories. 1 was “less than 3,500 people”; 2 = “3,500 to 7,000”; 3 = “7,000 to 25,000”; 4 = “25,000 to 100,000”, and 5 was “more than 100,000.”

Age and gender . Age was a continuous variable measuring the ages of respondents, and gender was recorded as 0 = female and 1 = male.

Education . Five categories of formal education levels were provided to choose from, ranging from “less than high school” to “advanced degree.”

Residence region . The two bottled water questions of interest were asked in the following regions and states, which include several states of the southeast region (Region 4: Alabama, Florida, Mississippi, Tennessee); the southern region (Region 6: Arkansas, Louisiana, Oklahoma, Texas); the Midwest Heartland region (Region 7: Iowa, Kansas, Missouri, Nebraska); the mountain region (Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming); and the southern Pacific region (Region 9: Arizona, California, Nevada [ 22 ]). Figure 1 gives a visualization of the above states and regions.

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Map of the Sampled Regions and States.

Secondly, we applied a logistic regression on the regular bottled water users. With this part of analysis, we focused on the respondents who used sources other than bottled water for primary drinking purposes but reportedly often used bottled water for drinking. The hypothesis to be tested with this model is the second one, and the independent variable of primary interest is water supply type, which has three categories: 1 = private supply (private well, river, pond, lake, etc. ), 2 = public municipal supply, and 3 = small water supply systems (including rural water district and community well). All the other independent variables used in the previous model were also included in this logistic regression model.

3. Results and Discussion

3.1. descriptive summary of the sample.

The demographic distribution of survey respondents was similar to that reported for the general adult population based on the 2000 US census data for the demographic factors of community size, age (adult population), and formal education level. The only factor not in line with 2,000 census data was gender. Here, male respondents were much more heavily represented compared to the general population as a whole (about two thirds of the respondents were male, see Table 1 ). Even though 50% of the mailed surveys were addressed to females, it was apparent that the male adult in the surveyed household was more likely to respond to the survey [ 20 ]. The summary of sample statistics is shown in Table 1 below.

Summary Statistics.

Over 13% of all respondents reported that they used bottled water as the primary source for drinking water, while 45.4% of all respondents said they often used bottled water for drinking. The mean for surface water quality perception was 1.99 (fair), and the mean for ground water quality perception was 2.22 (slightly above fair), a little higher than that of surface water. About fifteen percent respondents said they felt their home drinking water was not safe to drink. This percentage corresponded well to the percentage of respondents that used bottled water as their primary drinking source. On a scale of 1 to 10, average environmental attitude score was 5.76, and responses tended to cluster in the middle of the 1 to 10 scale. Thirty-five percent respondents marked their environmental view as 5, midway between totally eco-centric and totally anthropocentric. Other responses with higher percentage are 4 (9%), 6 (15%), and 7 (16%). About 12% respondents responded with higher scores (8–10), and the lower extreme scores (1–3) are only 6% of the total responses. This represents a balanced, somewhat more pro-environmental view towards the relationship between protection of nature and human use of natural resources. Mean age of the survey respondents was 56.8, while average formal educational achievement was between “some college” and “college degree.” About two thirds of the respondents were male.

3.2. Logistic Regression Model 1: Primary Bottled Water Users

Our first model used a logistic regression model to examine the relationship between primary bottled water users and water quality perceptions ( Table 2 ).

Logistic Regression for primary bottled water users (N = 3,232).

We found that groundwater quality perception was a significant predictor. As the ground water quality perception increased by one ascending-ordered category, the odds of a person using bottled water as primary source of drinking water was reduced by 33%. Compared with a person who feels their home water is safe to drink, a person who does not trust their home drinking water safety was more than 4.8 times more likely to use bottled water as their primary source of drinking water. However, there was no significant difference in bottled water use among respondents with different surface water quality perceptions. Environmental attitudes were not a significant predictor for primary bottled water use.

Age and gender were also found to be significant predictors for bottled water use. When all other conditions were exactly equal, a respondent who was one year older in age was about 2% less likely to use bottled water as the primary source of drinking water. From a gender standpoint, the odds that a female uses bottled water for primary drinking source are 1.32 times as much as the odds for a male, with all other conditions being equal. Education level was not a significant predictor for bottled water use.

Place of residence was found to have important effect on the use of bottled water. For example, community size had a positive relationship with being a primary bottled water user. As the community size increased by one ascending category, the odds of the resident of larger community using bottled water for primary drinking purposes were increased by 0.116 times. The use of bottled water as primary source of drinking water was also closely related to where the respondents lived in the U.S. For example, a respondent in the Midwest (region 7), when compared with a respondent living in the southern Pacific region (region 9), was over 80% less likely to be a primary user of bottled water. Similarly, for a respondent in the mountain region (region 8), the odds of the person using bottled water as primary drinking water source were reduced by 53% compared with a resident in the southern Pacific region (region 9). Similar to the southern Pacific region (region 9), the southern region (region 6) and the southeast region (region 4) also have more residents primarily depending on bottled water for drinking (see appendix for detailed regional bottled water use comparison).

With logistic regression models, there is no equivalent r-squared statistics to show the explained variability in the dependent variable. However, the pseudo R 2 shows that the explanatory variables have moderate strength of associations with consumption of bottled water. The model non-significant chi-square test and likelihood ratio test statistics (1.0), which suggests good model fit [ 23 ].

Overall, this model shows that U.S. consumer perceptions about groundwater quality have strong associations on the purchase of bottled water for drinking. This suggests that bottled water use may be considered a substitute for other water sources when groundwater quality is perceived to be poor.

3.3. Logistic Regression Model 2: Regular Bottled Water Users

A second logistic regression model was used to predict regular users of bottled water ( Table 3 ).

Logistic Regression for regular bottled water users (N = 2,850).

These results show similar patterns as with primary bottled water users found in Table 2 . Groundwater quality perception, safe drinking water perception, age, gender, and region of residence were found to be significant predictors. Community size, however, unlike in the first regression model, was not significant. The likelihood of private water supply users being regular bottled water users was about 25% less than that of small water supply system users. There were no significant differences in bottled water use between municipal water supply users and small water supply system users.

The pseudo r-squared statistics are relatively small compared with our first model, which suggests that the same independent variables do not have particularly strong correlations with or explaining power for regular bottled water usage, although the chi-square test statistic is still non-significant.

3.4. Discussion

With findings of both logistic models, we confirmed the hypothesized negative association between perception of ground water quality and bottled water use. Given that an estimate of 49% of the U.S. population depends on groundwater for its drinking water supply from either a public source or private well [ 24 ], the groundwater quality perception seems to explain the consumers’ behavior regarding bottled water. Perception of drinking water safety is found to be highly associated with bottled water use. The findings about water quality perceptions generally confirmed that when public doubts about the safety of their tap water, they look for alternatives like bottled water [ 6 , 14 ]. No significant relationship, however, was found between surface water quality perception and bottled water use.

Our data do not include actual water quality or safety conditions so it is not known whether consumer’s perceptions of the condition of their local drinking water are accurate reflections of the real water quality or not. If perceptions are accurate, then community leadership along with regulatory agencies needs to act to correct the problems for public health to be maintained. However, one might ask why consumers have turned to bottled water purchases rather than voice their concern and pressure public water departments and elected officials for solutions. This is particularly relevant since it is public municipal and rural water system supply users rather than private water supply users that are likely to purchase bottled water. Public water systems are tax supported, regulated and maintained under much more rigorous monitoring and testing conditions than bottled water manufacturers. This suggests that if a large number of consumers purchase drinking water as a substitute for public tap water, they can undermine the water infrastructure investments needed to assure safe public water supplies. This has implications for community capacities to provide low cost, accessible, and safe drinking water for their entire population. Without safe public water supplies, limited income households’ health and well-being are at risk.

Our findings show that although municipal water supply users and small water supply users were equally likely to be regular bottled water users when every other condition is held the same, private water supply users (private well or surface water sources) were less likely to use bottled water than small water supply users. Consumers on private wells are often targets of public health campaigns reminding them to have their water tested regularly. To the extent this happens, private water supply users may believe they have more knowledge of and control over the quality of their water supply and thus trust it. Also, media coverage and increased headlines concerning problems with public water systems around the world can lead to high distrust (appropriately) of local water supplies [ 14 ]. The poor water conditions also increase the cost of treating water in public systems so that it is safe for consumption. This can lead to changes in water taste despite being safe to drink after treatments. While substituting bottled water for public tap water under these circumstances may be a short term “fix”, it does not address long term problems of water quality or the effect it has on escalating the cost of public water as increased treatments become necessary.

Residents of larger communities were found to be more likely to be primary bottled water users, which means that a higher proportion of population in larger communities tend to depend on bottled water rather than their tap water for drinking purpose. Note that this association is established when other conditions are controlled for. That is, for two persons in the same region, with the same perceptions towards their drinking water, surface and ground water quality, and having exactly the same demographic characteristics (age, gender, education), the person from larger community is more likely to depend on bottled water for drinking purpose. As some researchers have suggested, factors like media hype about water supply problems, commercial campaigns on bottled water, or even peer pressure for more fashionable ways of drinking all contribute to bottled water consumption [ 6 , 14 ]. And considering that these factors are usually stronger in larger cities, it is likely that people in larger cities have more negative feelings about their water supply systems and turn to bottled water for solution. However, if respondents were already using some sort of water supply for drinking purpose, then there is no significant association found between their community size and whether or not they regularly consume bottled water. With limited information in our data we were not able to fully explain the associations found between community size and bottled water consumption, and we suggest future research look at community level variables for possible answers.

Our data also show that younger people and females are more likely to purchase bottled water. Young people are generally believed to be more susceptible to marketing and advertising, which are essential keys held by the bottled water companies [ 6 , 14 ]. And the higher likelihood of female drinking bottled water is consistent with previous literature on gender differences in risk, especially health and food related risk perceptions [ 25 , 26 ]. The findings about more consumption in these two groups of people suggests a need to target these audiences with messages about the importance of learning about their local water quality as well as the costs and quality differences between bottled water and public drinking water supplies.

Our hypothesis about environmental attitudes was not supported by the data. The relationship between environmental attitudes and bottled water use was not significant. Consumers with stronger overall concern about the environment do not seem to transfer this concern to pollution and waste problems associated with purchasing bottled drinking water. But again, because of the relatively longer cycle of research using multistate data (data collection in some states were done back in 2004), our data might not be able to reflect the newest trend of national environmental concern on bottled water.

Finally, the hypothesized regional effect regarding bottled water use was confirmed by the data. Residents of the Midwest and west mountain regions were far less likely to use bottled water for either primary drinking purpose or other occasions of regular uses, while residents of the southern pacific, the south, and the southeast were all equally likely to be bottled water users. This suggests that other variables such as culture, actual water quality conditions, media coverage of water issues and other place specific factors may be influencing the decision to use bottled water versus tap water from a private or public system. Water resource quantity and income might also be driving forces for the differences. Further research is needed to better explain regional variations.

4. Conclusions

Water is essential to human health and life. Access to safe water supplies and affordability are central concerns of public health and individual consumers. In this study we find that perceptions of ground water quality and local water supply safety are associated with decisions to purchase bottled water versus use public water systems for drinking water. When local water is not considered safe or of high quality U.S. consumers are more likely to use bottled water as a primary water source. Furthermore, negative perceptions of safety increase the likelihood of a consumer frequently purchasing bottled water regardless of whether their primary source of drinking water is a small water system or large municipal water supply system.

Two key implications of our findings are that (1) public health officials and community leaders need to work to assure that public municipal drinking water supplies are safe; in addition, they should find effective ways to communicate to local residents the safety of their water supply; and (2) environmental leaders and activists need to campaign about the long lasting impacts of plastic water bottles. Further the public must be engaged in understanding the relationship of water quality to the capacity of local water systems to maintain safety and good taste standards. Consumer distrust of their groundwater quality should be leveraged to create community action to address legitimate concerns.

Acknowledgments

This research was partially funded by the National Institute of Food and Agriculture (NIFA), U.S. Department of Agriculture (USDA) under agreement 2008-51130-19526 also known as the Heartland Regional Water Coordination Initiative, the Iowa Agriculture and Home Economics Experiment Station, and USDA agreement 2008-51130-0474, also known as the Pacific Northwest Regional Water Resources Coordination Project.

A separate analysis, a one-way ANOVA (analysis of variance) was done to compare regional differences in bottled water use for primary drinking purposes. Table 1 shows bottled water use in each region and differences with statistical significance. The variable (primarily purchase bottled water for drinking) is a dichotomous variable with two possible responses 0 (not purchase) and 1 (purchase bottled water for drinking). Therefore the following means reflect proportion of respondents responding with 1 in each region. Post-hoc Bonferroni pair tests were conducted on the means and the last column of the following table shows regions with significant differences (at 0.05 level). For example, the first row shows that region 4 has mean which is significantly different from that of region 6, 7, 8, and 9, respectively.

Bottled water use by region.

Region 9 and region 6 have significantly higher percent of primary bottled water users, followed by region 4. Region 7 and region 8 have the least primary bottled water users.

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Open Access

Peer-reviewed

Research Article

The impact of water consumption on hydration and cognition among schoolchildren: Methods and results from a crossover trial in rural Mali

Roles Formal analysis, Writing – original draft

Affiliation Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, Georgia, United States of America

Roles Data curation, Investigation, Methodology, Project administration, Supervision, Writing – review & editing

Roles Methodology, Resources, Writing – review & editing

Affiliation School of Psychology, University of East London, London, United Kingdom

Roles Project administration, Supervision, Writing – review & editing

Affiliation Monitoring, Evaluation, and Learning Section, Save the Children Mali, Bamako, Mali

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing

* E-mail: [email protected]

Anna N. Chard,
Victoria Trinies,
Caroline J. Edmonds,
Assitan Sogore,
Matthew C. Freeman

Published: January 17, 2019
https://doi.org/10.1371/journal.pone.0210568
Reader Comments

Adequate provision of safe water, basic sanitation, and hygiene (WASH) facilities and behavior change can reduce pupil absence and infectious disease. Increased drinking water quantity may also improve educational outcomes through the effect of hydration on attention, concentration, and short-term memory. A pilot study was conducted to adapt field measures of short-term cognitive performance and hydration, to evaluate levels of hydration, and to investigate the impact of providing supplementary drinking water on the cognitive performance of pupils attending water-scarce schools in rural Mali. Using a cross-over trial design, data were collected under normal school conditions (control condition) on one visit day; on the other, participants were given a bottle of water that was refilled throughout the day (water condition). Morning and afternoon hydration was assessed using specific gravity and urine color. Cognitive performance was evaluated using six paper-based tests. Three percent of pupils were dehydrated on the morning of each visit. The prevalence of dehydration increased in the afternoon, but was lower under the water condition. Although there was a trend indicating drinking water may improve cognitive test performance, as has been shown in studies in other settings, results were not statistically significant and were masked by a “practice effect.”

Citation: Chard AN, Trinies V, Edmonds CJ, Sogore A, Freeman MC (2019) The impact of water consumption on hydration and cognition among schoolchildren: Methods and results from a crossover trial in rural Mali. PLoS ONE 14(1): e0210568. https://doi.org/10.1371/journal.pone.0210568

Editor: Michael L. Goodman, University of Texas Medical Branch at Galveston, UNITED STATES

Received: January 24, 2018; Accepted: December 27, 2018; Published: January 17, 2019

Copyright: © 2019 Chard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: Funding was provided by the Emory University Research Committee ( http://www.urc.emory.edu/grants/urc/index.html ). MCF received funding (grant number N/A). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Health and educational benefits associated with improved water, sanitation, and hygiene (WASH) in schools include reduced diarrhea, absence, acute respiratory infection, and soil-transmitted helminth infection [ 1 – 5 ]. The availability of water during the school day is essential for supporting personal hygiene, sanitation, and maintaining a clean school environment. Increased access to water for drinking at school may also directly affect pupils’ academic performance through the cognitive benefits associated with decreased dehydration [ 6 – 8 ].

A recent UNICEF report found that only 53% of schools in least developed and other low-income countries had access to adequate water facilities, highlighting a gap in access to year-round, reliable, and safe water supply in sufficient quantities to support students’ needs [ 9 ]. Two studies assessing dehydration prevalence among school-age children living in hot, arid regions found that approximately two-thirds of children were in a state of moderate to severe dehydration [ 10 , 11 ].

The impact of dehydration on cognitive performance is well studied among adults in experimental settings. Dehydration induced through exercise or heat stress has been associated with decreased short-term memory [ 6 , 8 ], long-term memory [ 8 , 12 ], arithmetic efficiency [ 6 ], visuospatial function [ 6 ], and attention [ 7 ]. Few studies have investigated the relationship between dehydration and cognition in children. Evidence from three intervention studies in the United Kingdom corroborate findings among adults, suggesting that drinking water was associated with better scores of attention [ 13 , 14 ], short-term memory [ 14 – 16 ], and visual search [ 13 ]. However, these studies did not collect biometric measures of hydration status. Two additional studies conducted among children in Israel and Italy that assessed hydration status through urine osmolality found that dehydration was associated with decreased short-term memory [ 10 , 16 ].

Linking drinking water availability directly to cognitive skills among children in water-scarce areas would have important public health and policy implications. A deeper understanding of the relationship between hydration and cognition could provide significant and novel evidence for the importance of improving water access in schools. Here, we aim to address the gaps in existing literature by assessing the relationship between water consumption, hydration, and cognition in a setting where children do not commonly have water access during the school day.

We assessed the prevalence of dehydration among children attending schools in Mali, West Africa, and examined the effect of drinking supplementary water during the school day on hydration status and on cognitive test scores. Our hypothesis was that the majority of students would be dehydrated and that the provision of supplementary water would be associated with improved hydration and improved cognition. Methods included the piloting and refining of cognition measurements that had not been previously used in sub-Saharan African field settings. In addition, to our knowledge we collected one of the first sets of data indicating biometric levels of dehydration and reporting on the cognitive effects of dehydration in sub-Saharan Africa or elsewhere in the global South, where access to water is the poorest.

Materials and methods

We conducted a pilot study to investigate the impact of providing supplementary drinking water on the cognitive performance of pupils in water-scarce schools in rural Mali. The purpose of this study was to 1) pilot measures of short-term cognitive performance, 2) pilot field measures of hydration, 3) pilot data collection procedures for potential inclusion in a larger trial, 4) evaluate levels of dehydration among primary school students in water-scarce settings, and 5) test the association between drinking water and hydration on various measures of cognitive performance.

Data collection took place between January 7–10 and March 4–7, 2013 at two rural primary schools within 20 km of Sikasso town, Mali. Data collection at the second school was delayed due to armed conflict within the country. The maximum high temperature for data collection was 29°C in January and 40°C in March.

School eligibility, school selection, and participant selection

Schools were eligible for inclusion if they had no water point access within 0.5 kilometers, were within 1.5 hours drive from Sikasso town, and had at least 60 students in grades three through six. Two schools meeting eligibility requirements were purposively selected based on logistical considerations.

A total of 120 pupils in grades five (ages 9–13) and six (ages 10–16) were recruited. At each school, 30 pupils from each grade were randomly selected from school rosters using random number lists. In the event a pupil was absent or did not wish to participate, we continued to select pupils randomly from the class rosters until a sample size of 30 was reached for each grade.

Study design

We employed a crossover trial design in which each pupil in the study served as his or her own control. A crossover design was selected over a randomized controlled trial design due to the logistical challenge of randomizing water distribution within classrooms. Given the novel study procedures, crowded school setting, and limited timeframe, we were not certain that we could ensure water was not shared between pupils in intervention and control groups.

Hydration and cognition measurements were collected on two different days at each school. On one of the visit days we collected data without changing any conditions at the school (the control condition). On the other visit day we provided all pupils, regardless of participation in the study, with a 1.5 litre bottle of water in the morning, encouraged them to drink throughout the day, and refilled their bottle upon request (the water condition). We did not track the amount of water each pupil consumed. To account for confounding due to becoming familiar with the test (henceforth referred to as “practice effect”), the order of intervention days was counterbalanced between schools so that one school received water on the first day, while the other received water on the second day. Additionally, we included a separation of three days between visits.

To evaluate potential confounders or effect modifiers of hydration and cognition, participants were asked if they had anything to eat or drink that morning and reported drinking water availability at school. Staff members also made observations of drinking water availability at the school on the day of the visit. The majority of pupils went home at noon and returned for afternoon classes. We did not record lunch practices.

Measures of hydration

We collected three measures of hydration: urine specific gravity (U sg ), urine color (U col ), and self-reported thirst. Both U sg and U col are inexpensive measurements that can be easily conducted in the field with minimal training. They are strongly correlated with urine osmolality [ 17 , 18 ], a common measure of hydration in non-laboratory settings [ 10 , 11 , 16 ]. U sg measures urine density compared with water and was measured with ATAGO MASTER-URC/NM urine specific gravity analog refractometers (model 2793, ATAGO U.S.A. Inc., Bellevue, WA) [ 18 ]. The refractometers were calibrated using distilled water and were recalibrated at least every 15 readings, according to manufacturer instructions. U col was measured against a validated scale of eight colors [ 17 , 18 ]. Two trained enumerators independently evaluated each sample, and re-evaluated the sample together if their independent values differed; a third trained enumerator was consulted if no consensus was reached. Self-reported thirst [ 13 , 19 ] was collected on a five-point pictorial scale based on the Wong-Baker FACES pain rating scale [ 20 ]. For analysis, the least-thirsty image was assigned a value of 5 and values decreased to 1 as reported thirst increased.

Pupils provided urine samples between 8 and 9 am and again between 2–3 pm on each day of data collection. All urine analyses were conducted on the school grounds by trained study enumerators. Pupils self-reported thirst in the afternoon, after the completion of cognitive testing.

Measures of cognition

Cognition was measured using six tasks that assessed visual attention, visual memory, short-term memory, and visuomotor skills. These tests were taken from previous research on hydration and cognition that was conducted with children in Israel and the United Kingdom [ 10 , 13 , 14 ], piloted in Mali, and adapted to the Malian context.

Letter cancellation.

This test assesses visual attention . Pupils were given a grid containing target letters randomly dispersed among non-target letters and were given one minute to cross out as many target letters as possible. Scores were calculated by subtracting the number of non-target letters identified from the number of target letters identified; the maximum test score was 38.

Direct image difference.

This test assesses visual attention . Two nearly identical pictures were presented side-by-side. Pupils were given one minute to circle differences between the two images. Scores were calculated by subtracting the number of incorrect differences identified from the number of correct differences identified; the maximum test score was 9.

Indirect image difference.

This test assesses visual memory . Two nearly identical pictures were presented in sequence. Pupils were given ten seconds to study the first image. They were then briefly presented with a blank page, followed by a second image, and given one minute to circle the differences between the two images on the second image, without returning to the first. Scores were calculated by subtracting the number of incorrect differences identified from the number of correct differences identified; the maximum test score was 9.

Forward digit recall.

This test assesses short-term memory . Twelve sequences of numbers two to seven digits in length were read aloud to pupils at a rate of one number per second. Pupils were asked to write down the sequence in order after the sequence was read aloud. Two scores were derived from this test: the total number of correctly recalled sequences (maximum score of 12) and the maximum digit span of the correctly recalled sequence (maximum score of 7).

Reverse digit recall.

This test assesses short-term memory . Ten sequences of numbers two to five digits in length were read aloud to pupils at a rate of one number per second. Pupils were asked to write down the sequence in reverse order after the sequence was read aloud. Two scores were derived from this test: the total number of correctly recalled sequences (maximum score of 10) and the maximum digit span of the correctly recalled sequences (maximum score of 5).

Line tracing task.

This test assesses visuomotor skills . Pupils were presented with two curved parallel lines. They were given fifteen seconds to draw a line between them as quickly as possible while attempting not to touch the printed lines. Scores were calculated by subtracting the number of times the pupil’s line touched the side from the total length of the line in centimeters; the maximum test score was 29.

All cognitive tests were paper-based and administered by trained study staff in a group setting within the school classrooms. Testing sessions were standardized using written scripts. Staff introduced each test with a scripted explanation and an example, with no breaks between tests. Testing sessions lasted a total of 60–75 minutes and began at 3:00 pm in the afternoon of each visit. Each pupil in the study completed the testing session twice, once on the control condition day and once on the supplementary water condition day. Four parallel versions of each test were developed so that individual pupils did not receive the same test twice and pupils sitting next to each other did not receive the same test. All four test versions were distributed at each testing session. Tests were independently graded by two different staff members using fixed criteria. Grading criteria also provided guidelines to indicate whether or not pupils understood the tasks according to instruction. Tests with conflicting scores were examined by the study coordinator, who decided the final score for the task.

Data analysis

Data were entered into MS Excel and analyzed using STATA 13 SE. We tested both the impact of treatment condition (whether student was provided water or not during the day) and hydration status on change in test score. U sg was used to test the impact of hydration on change in test score because it was the only of our three hydration measures based on biomarkers, and is the most accurate of those three measures of hydration status [ 21 ]. A higher U sg indicates increased dehydration. Pupils were classified as dehydrated if they had a U sg of 1.020 or higher, which is equal to the dehydration threshold of urine osmology>800 mOsmol kg-1 H 2 O that has been used in previous studies of dehydration among children [ 10 , 11 , 16 ]. A total of eight scores for the six cognitive tests were calculated according to grading criteria. Scores were coded such that higher test scores on all cognitive tests represented better performance.

Univariable analysis

As proof of concept of the effect of water provision on hydration, we evaluated univariable differences in morning and afternoon hydration, U sg , and U col by treatment group using McNemar’s test statistic (binary variables) and paired sample t-tests (continuous variables). To evaluate the correlation between U sg , U col , and self-reported thirst, as well as the correlation between each of the cognitive test scores, pairwise tests of correlations between cognitive test scores were conducted using the pwcorr command. Lastly, to measure the presence of a “practice effect,” paired sample t-tests were used to assess differences in cognitive test scores between school visits.

Multivariable analysis

We examined the association between the provision of supplementary drinking water (treatment) and cognitive test scores as well as the association between pupil hydration (regardless of treatment) and cognitive test scores. These associations were assessed using separate mixed-effects linear regression models, where each cognitive test was the outcome, while treatment condition or hydration status, respectively, was the predictor covariate. Models included a random intercept at the pupil level to account for pupils acting as their own control. Unstandardized Beta coefficients are presented.

All models adjusted for multiple comparisons using the Bonferroni correction; as such, associations were considered significant if they had a p -value <0.006, the alpha necessary to reach 95% significance with eight hypotheses. Models were assessed for interaction and confounding with the following variables chosen a priori : pupil sex, pupil grade, reported drinking in the morning, reported eating in the morning, reported thirst, and morning hydration.

Interaction was assessed by running models of each cognitive test outcome with each predictor variable, potential interaction covariate, and an interaction term for the predictor and covariate (e.g. treatment*sex). Some variables initially indicated interaction at p <0.05. However, after adjusting for multiple comparisons using the Bonferroni correction, the only effect modifier to retain significance was pupil sex, which modified the relationship between afternoon dehydration and forward number recall- maximum digit span test score. Stratified results from this model are presented. All other associations were then tested for confounding; covariates significantly associated with the predictor variable as well as the outcome variable in independently run fixed-effect models were considered to be confounding variables. At p = 0.006, grade confounded the association between treatment and direct image difference & indirect image difference test scores, so was included as a control variable in these models. All models controlled for the visit day in order to account for a “practice effect” on cognitive tests.

We compared models from all pupils to models that excluded scores from pupils who did not complete cognitive tests according to instruction. There were no significant differences between model results, thus, we present the former results in order to maximize sample size. Only students with complete data for all measures of interest were included in analysis. We dropped 13 pupils due to absence on the second day of data collection, not being able to provide a urine sample, or inability to match pupils test scores and hydration measures due to improper identification procedures.

This study was approved by Emory University’s Institutional Review Board (IRB00062354), the Mali Ministry of Education, and the National Technical and Scientific Research Center ( Centre National de la Recherche Scientifique et Technique ) in Mali (001/2013-MESRS/CNRST). All three institutions approved consent in loco parentis (in the place of parents) due to the logistical challenges of finding and contacting parents in their homes, risk of lost wages to parents if they were summoned to school, and low levels of literacy making letters unfeasible. Permission for study activities and approval of a waiver of parental consent was also obtained from the Centres d’Animation Pédagogique (Center for Pedagogical Activity) and Académie d’Enseignement (Academy of Education) in Sikasso, both local government representatives responsible for education in the area where the study was conducted. Prior to commencing study activities at each school, we obtained consent in loco parentis from the school director and the Comité de Gestion Scolaire (school management committee), the organization empowered to oversee management and activities at the school, on behalf of the community that school serves. Pupils who were selected for the study provided informed verbal assent in a private setting prior to the start of data collection activities.

Study population

Data were collected from 120 pupils in two schools; of these, 107 (89.2%) pupils had complete data and were included in analysis. The sample was initially comparable in terms of sex, grade, and school. After removing pupils with incomplete data (n = 13), the final sample included 46 (43.0%) girls, 61 boys (57.0%); 58 (54.2%) pupils from grade five, 49 (45.8%) pupils from grade six; 47 (43.9%) from School 1, and 60 (56.1%) from School 2. The mean (sd) age was 11.6 (1.0) years in School 1 and 12.1 (1.7) years in School 2.

Univariable estimates of association with hydration

Only 3% of pupils were classified as dehydrated in the morning according to U sg (U sg >1.019), regardless of visit day or study condition. The difference between water and control condition mean morning U sg or U col was not statistically significant, and we found no difference in the prevalence of dehydration prior to distribution of water.

Pupils became more dehydrated throughout the school day under both study conditions. There was no significant difference in U col , self-reported thirst, or the prevalence of pupils classified as dehydrated in the afternoon under the water condition compared to the control condition. However, mean afternoon U sg was significantly higher under the control condition compared to the water condition ( Table 1 ). U sg and U col were strongly correlated both in the morning (r = 0.777, p <0.001) and afternoon (r = 0.734, p <0.001). Self-reported thirst, which was only measured in the afternoon, was not significantly correlated with either afternoon U sg (r = 0.089, p = 0.20) or afternoon U col (r = -0.003, p = 0.97).

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https://doi.org/10.1371/journal.pone.0210568.t001

Univariable estimates of association with cognition

Results from pairwise tests of correlations between cognitive test scores and results from the paired t-tests of the association between test score and visit day are shown in Table 2 . Most tasks were significantly correlated with at least one other task included in the battery of cognitive tests. Students achieved significantly higher scores on the second visit compared to the first visit for six of the eight cognitive tests, regardless of treatment condition.

https://doi.org/10.1371/journal.pone.0210568.t002

Multivariable estimates of association between cognitive test scores and treatment condition

In adjusted models, the provision of supplementary drinking water was significantly associated with two cognitive tests: reverse number recall (total) and line trace. Under the water condition, pupils performed better on the reverse number recall test. However, pupils had lower scores on the line trace test under the water condition ( Table 3 ).

https://doi.org/10.1371/journal.pone.0210568.t003

Multivariable estimates of association between cognitive tests scores and hydration status

We examined the impact of hydration on cognitive test performance, regardless of treatment condition. Neither hydration status, where a U sg greater than 1.019 indicated dehydration, nor U sg were significantly associated with any cognitive test score ( Table 3 ). The test for interaction indicated that pupil sex significantly modified the association between forward number recall (maximum) and afternoon dehydration. When stratified by sex, males performed worse when dehydrated (β = -0.14; 95% CI -0.54, 0.27; p = 0.501) and females performed better when dehydrated (β = 1.10; 95% CI 0.31, 1.89; p = 0.006); only the association between hydration and forward number recall among female pupils approached statistical significance.

We conducted a cross-over trial as part of a pilot study to examine the associations between water consumption, hydration, and cognition among pupils attending water-scarce schools. We successfully adapted measures of cognitive performance that could be completed by children in rural Malian schools and tested the feasibility of field hydration measures and data collection procedures within schools in Sub-Saharan Africa. Results demonstrated that supplementary water provision within a school setting significantly decreased U sg , even within a short time period. However, we found no effect of the impact of supplementary water provision on cognitive test scores.

This research refined a battery of cognitive tests for use with children in Mali which can be adapted to other developing settings. Research conducted in the U.K. concluded that their cognitive test of visual memory was too easy for the target population, indicated by many children achieving the maximum score on the test, and thus modifying study results [ 13 ]. Our results show that the percentage of children achieving the maximum score or the minimum score on any of the cognitive tests ranged from 0.5%-15.4% and 0.5–4.2%, respectively, indicating that the cognitive tests adapted for this trial were neither too difficult nor too hard. However, results from our pairwise tests of correlation indicate that the two tests measuring visual attention (letter cancellation and direct image difference) were not significantly correlated, suggesting that further adaptation may be needed on these tests to measure this target skill. Furthermore, while scores for each of the four tests measuring short-term memory were significantly associated with at least one other score in the suite of tests measuring that domain, they were very similar tests in that they all incorporated number recalls. Thus, correlation does not necessarily indicate that they were in fact measuring the cognitive skill they were intended to measure.

This is one of the first studies to employ existing field methodology to collect urine samples and measure dehydration among school children in low-resource school settings. Results from this pilot study were further refined in a subsequent trial in Zambia [ 22 ]. Prior research on dehydration among schoolchildren has relied predominantly on self-reported thirst as their measure for dehydration. Although evidence- particularly among healthy individuals- is limited, research has concluded that one’s thirst response is not an accurate measure of hydration [ 23 , 24 ]. We found no research investigating this association among children. Our results demonstrated no significant difference between self-reported thirst among pupils under the water condition compared to the control condition, even though the measurements of U sg indicated that pupils under the water condition had significantly higher levels of hydration than pupils under the control condition. Additionally, self-reported thirst and the biometric measurement of U sg were not significantly correlated. These findings support previous literature concluding that self-reported thirst is not an accurate measure of hydration. Given our findings, future research should consider utilizing only measurements that provide biometric evidence of dehydration. Data also revealed that U col , although strongly correlated with U sg , did not capture a significant difference in afternoon hydration between water and control conditions. We believe this may have been due to the subjective nature of matching urine color to the color chart. The use of refractometers to measure U sg required less training and took less time than measuring U col , and thus is recommended for future studies investigating dehydration levels of subjects in low-resource settings.

Our finding that only 2.8% of pupils were dehydrated in the morning stands in stark contrast to previous research which reported that 84% of Italian school children [ 16 ], 68% of Israeli school children [ 11 ], and 43% of Zambian schoolchildren [ 22 ] were dehydrated at the beginning of the school day. While this result was initially surprising, it may be partly explained by evolutionary mechanisms. In their research, Bar-David reported that among their sample of Israeli schoolchildren, Bedouin children, who originate from a population that has lived in the desert for many generations, had the lowest mean urine osmolality (the lowest prevalence of dehydration), possibly because their bodies adapted over time to have a lower threshold of thirst [ 10 , 11 ]. Thus, Malian children, who reside in hot, arid, and water-scarce environments, may have also adapted a greater resistance to dehydration, leading to a lower prevalence of dehydration at the beginning of the school day. Extremely low levels of morning dehydration may also be partly explained by the fact that a vast majority of students (93%) reported drinking something in the morning before going to school. We do not believe that pupils intentionally consumed more water than usual in preparation for participation in the research. Neither school officials nor pupils were aware of the study topic, activities, or pupil selection prior to the first day of the study. Thus, participants would not have had the foreknowledge to alter their normal drinking behaviors. Although school officials and pupils were aware of the date of the second visit, given that no significant differences in the prevalence of dehydration or U sg were observed between the first and second visits, it is unlikely that students changed their drinking practices for the second day.

Under both treatment conditions, dehydration increased throughout the day. Pupils had significantly lower U sg in the afternoon under the supplementary water condition than under the control condition, demonstrating the “proof of principle” that supplementary water provision improves hydration. However, there was no significant difference in the prevalence of afternoon dehydration among pupils in the water group compared to pupils in the control group. Nonetheless, when the significant impact of water consumption on increasing U sg is considered in light of findings of the relationship between drinking water and cognition from other contexts [ 13 – 16 ], there is evidence that providing drinking water at school may create a positive impact on pupil learning.

We found some evidence that supplementary water provision was associated with higher scores on cognitive tests, but few results were significant. These results are consistient with those from our follow-up trial among primary school children in Zambia [ 22 ]. Treatment was significantly associated with higher scores on the letter cancellation task, a result supported by previous literature that also found a positive relationship between provision of drinking water and performance on visual attention tasks [ 14 , 22 ]. While previous studies have reported no significant association between water provision and visuomotor skills [ 13 , 14 ], we found that scores on the line trace test were significantly, but negatively associated with supplementary water provision. Although this result was unexpected, it may be largely explained by a practice effect, in which pupils performed significantly better the second time they took the test, regardless of treatment condition. Although pupils took a different version of the test on each day, a practice effect was evident, as test scores significantly improved when pupils performed each task the second time. One possible reason for this difference could be that pupils in Mali are not accustomed to the types of activities performed during the tests, which were adapted from tests used in Western settings. Although the distribution of test scores and the correlation of tests measuring the same domain do indicate that the tests were suitably adapted to the context, the novelty of the tests may have caused a much lower baseline score at the first testing session. Pupils may need to practice completing the tasks several times in order to fully understand the tests before their scores are measured.

Lastly, evidence on the degree and duration of dehydration necessary to impact cognitive performance is limited. It is possible that the lack of significant improvements in cognitive performance following treatment is because one school day of supplementary water provision is not sufficient to reverse the impacts of chronic dehydration and impart cognitive benefits on schoolchildren; perhaps more long term water consumption is necessary for these benefits to be measurably improved [ 22 ]. Further, although the U sg data provide evidence that pupils drank under the treatment condition, we did not measure the volume of water consumed by subjects. Measuring the volume of water consumed by subjects and including a dose-response measure in the analysis could contribute to the discourse on how much water consumption is needed to improve hydration, and how much hydration is needed to improve cognition.

Limitations

There are several limitations to the current research. First and most crucial was the impact of the practice effect, in which pupils performed significantly better on cognitive testing during the second visit, regardless of treatment condition. Approaches to limit or account for the practice effect on cognitive testing in primary school populations residing in settings where this type of testing is uncommon requires additional attention; future research should focus on alternative trial designs to minimize this impact. Additionally, the fixed test order could have led to a learning effect across tests, where certain tests- conceivably later on in the series- revealed a more significant association due students becoming more comfortable with testing in general, rather than due to the skill tested. Students in both the intervention and control would have had the same learning effect, which would bias our results to the null, but there is no way to control for this within the individual models. However, we observed no trend where students performed differently on tests administered in the end of the suite on either testing day. Further, we reviewed the estimates of effect and do not find any effect modification. Second, because this was a pilot study, the sample was limited to 120 pupils in two schools. As such, the study may not have been sufficiently powered to detect significant but less strong impacts of supplementary water provision or hydration status on cognitive performance. Low levels of dehydration across study groups may have also further limited our ability to detect an impact. Third, we conducted an intention-to-treat analysis and did not measure or control for the volume of water consumed by the participants in the treatment group. We did not measure whether pupils in the control group consumed water brought from home, and we could not ethically restrict them from drinking water. We also did not record lunch practices among students, and cannot guarantee that children did not consume water when they went home for lunch. As such, we cannot unequivocally state that the intervention and control groups were separated by water consumption, or lack thereof. However, afternoon U sg was collected regardless of treatment condition, and results validate the degree of water consumption under treatment. Additionally, lunch practices among individual students would likely be similar across days, thus the influence of lunch practices would be consistent across test conditions since pupils act as their own controls. Fourth, due to external events, data collection at the second school was delayed for two months and occurred during a warmer period. The higher temperatures during the second data collection period may have impacted study results. Evidence suggests that exposure to heat may independently impact cognitive functions, however this research has not been conducted among children [ 25 – 27 ]. Although significantly more pupils in the second school were dehydrated in the afternoon compared to pupils in the first school, due to the crossover design, it is not possible to quantify the effect that temperature may have had on study outcomes. Last, the methodology, including the duration of tests, were adapted from cognitive tests previously used among primary school children [ 13 , 14 , 28 ], but the total testing time was longer than in previous studies due to the novelty of the tests in the population and our emphasis on explanation and examples. However, because there was no significant trend in scores across the testing suite, there is no evidence that performance worsened due to fatigue among students.

We suggest a two-step approach for collecting further evidence on hydration and cognition among pupils in water-scare schools. First, we recommend implementing a second trial with cognitive testing methodology that addresses the challenges of the practice effect in order to increase the evidence base on the link between hydration and cognition among schoolchildren in water scare areas. Once the link between improved hydration and cognition among schoolchildren has been established under experimental conditions, we recommend carrying out cross-sectional hydration testing in a larger sample of schools. Considering the apparent invalidity of self-reported thirst and the subjective nature of urine color evaluation, we recommend the use of urine specific gravity or another objective biometric measure for hydration testing. Given the evidence previously established, hydration in this case would serve as an easily quantified and measured proxy for pupil attention, memory, and concentration. Findings from this investigation could provide evidence of the benefit of drinking water access, and specifically on the construction of water points on school grounds, for pupils’ educational attainment.

Conclusions

This study represents novel research across multiple scientific disciplines and development sectors, and is an important step in developing clear and direct linkages between provision of WASH in schools and learning. Results demonstrated the proof of principle that increased water access improves hydration. Although we found no evidence for our hypothesis that improvements in hydration status leads to improvements in cognitive performance among pupils in water scare schools, results may have been masked by a strong practice effect, and the power to detect significant differences was limited. We demonstrated the feasibility of collecting biometric measurements of hydration status and testing cognitive abilities in resource-poor settings. Findings from this research and subsequent studies of hydration and cognition have broad significance for advocacy for international development and health sectors for increased attention to insufficient access to water supply for school children.

Supporting information

S1 file. data..

https://doi.org/10.1371/journal.pone.0210568.s001

Acknowledgments

This study was funded by the Emory University Research Committee. Additional in-kind support was given by Save the Children and Dubai Cares. We would like to thank Sarah Porter for assistance with development of the study, as well as Birama Diallo, Seriba Diallo, Makan Keita, Sadio Sangaré, and Mariam Traoré of Save the Children and Jérémie Toubkiss of UNICEF for their support.

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Impact of Pressure on the Deterioration of Drinking Water Distribution Networks

Published: 23 May 2024

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Amira Rjaibi 1 &
Sophie Duchesne ORCID: orcid.org/0000-0002-5619-0849 1

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Drinking water distribution systems must safely meet the expected demand for water. However, sudden pipe breaks can limit the continuous supply of drinking water. As operating pressure is among the factors affecting the probability of pipe breaks, a methodology was developed in this study to identify the pressure covariates that affect the frequency of water distribution pipe breaks. Five pressure covariates obtained from hydraulic simulations based on measured pressure and flow rate time series were evaluated using a likelihood ratio test to compare the maximum likelihood function values of a pipe break model calibrated with no covariates with those of the same model calibrated with a single pressure covariate. This pipe break model was calibrated using the recorded history of pipe breaks over a six-year period and applied to two district metered areas in the water distribution network of Quebec, Canada. The results indicated that the maximum and mean pressure covariates were significantly associated with the occurrence of pipe breaks.

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The Potential of RainWater Harvesting Systems in Europe – Current State of Art and Future Perspectives

A comprehensive review of sucker rod pumps’ components, diagnostics, mathematical models, and common failures and mitigations

A review of flood modeling methods for urban pluvial flood application

Data availability.

All data and models used during the study are proprietary or confidential in nature and may only be provided with restrictions as a confidentiality agreement has been signed with the municipality managing the studied water network. The pipe break model code can be provided upon request.

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Acknowledgements

The authors wish to thank the City of Quebec for providing the data and hydraulic model. Financial support was provided by the City of Quebec and the Natural Sciences and Engineering Research Council of Canada (NSERC; Grant RDCPJ 538446-18).

This work was supported by the City of Quebec and the Natural Sciences and Engineering Research Council of Canada (NSERC; Grant RDCPJ 538446–18).

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Both authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by A. Rjaibi under the supervision of S. Duchesne. The first draft of the manuscript was written by A. Rjaibi and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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• Computed pressure values for all pipes in two zones from inlet and outlet measurements.

• Calibrated a survival analysis pipe break model using break records from 2015 to 2020.

• Integrated different covariates in the model and applied a likelihood ratio test.

• The maximum and mean pressure were significantly associated to the occurrence of pipe breaks.

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Rjaibi, A., Duchesne, S. Impact of Pressure on the Deterioration of Drinking Water Distribution Networks. Water Resour Manage (2024). https://doi.org/10.1007/s11269-024-03892-y

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Hundreds of drinking water systems exceed new PFAS standards. It could grow to thousands.

After more than a year of collecting test results for toxic “forever chemicals,” the Environmental Protection Agency says almost 300 of America’s public drinking water systems – including some that serve hundreds of thousands of people – exceeded newly established annual limits.

That means these water utilities may need to start filtering their water or find new sources to comply with new rules limiting PFAS, or per-and polyfluoroalkyl substances. PFAS are nearly indestructible chemicals that have been shown to build up in human bodies, increasing the risk for certain types of cancer and other serious health complications .

USA TODAY recreated the EPA’s analysis and found public systems in Fort Worth, Texas; Fresno, California; Pensacola, Florida; and Augusta, Georgia, were among the hundreds whose sample averages landed above the new annual limits.

That number is bound to grow over the next two years as more water utilities submit their test results. Last month, the EPA estimated that one in 10 – or more than 6,000 – systems may eventually need to take some sort of corrective action to rid their water of PFAS.

Map: Where water systems reported PFAS contamination

This map shows water systems included in the EPA’s PFAS testing records, as of May 16, 2024. It’s based on boundaries developed by SimpleLab, a water-testing company. Points represent systems where the exact boundaries are not available. Enter an address to locate the nearest water systems. Then click on a system to review its PFAS measurements. Don't see a map? Click here.

Thousands of water systems have been testing for more than two dozen types of these compounds since January 2023 in the EPA’s most widescale effort ever to track PFAS’ spread across the country. 

Most public systems serving at least 3,300 customers must sample their drinking water either semiannually or quarterly throughout a single year and submit the results to the EPA.

These results represent single point-in-time measurements of PFAS, and the EPA wouldn’t require water systems to make changes unless a sample site’s running annual average surpasses the new limits. Plus, the agency is giving water systems five years to treat their water before it will enforce the new rule.

Almost 800 drinking water systems across the United States have recently measured PFAS at or above the newly established limits at least once, according to a USA TODAY analysis of data the EPA released last week .

Water from these systems eventually pours out of the faucets of approximately 47 million people.

Altogether, the EPA data now includes PFAS test results from 4,750 water systems. Over 1,000 were included for the first time in last week’s update, and they do show one bright spot: Many of the largest, newly added water systems haven’t detected any PFAS yet, including Los Angeles; Chicago; Tucson, Arizona; Boston; and Portland, Oregon.

How are water utilities getting PFAS out of their water?

Testing in Fort Worth, which relies on surface water drawn from a nearby lake, shows yearly averages for three separate PFAS chemicals topped the new limits at two of the city’s water treatment plants, according to USA TODAY’s analysis.

Mary Gugliuzza, spokesperson for Fort Worth Water, said the utility took action last summer with a PFAS treatability study “as soon as we were seeing numbers above” the then-proposed limits. She said they plan to go before the City Council as soon as next month to get a contract to begin designing a treatment process that uses granular activated carbon.

“We have been quite upfront that this is going to be expensive. I don't have an exact price tag for you,” Gugliuzza said. “We're going to seek any federal assistance that's out there to try and reduce the burden on our ratepayers. But we also know that there's not enough money for everybody out there, and a lot of people are going to be seeking this.”

Sample results from Emerald Coast Utilities Authority in Pensacola show the yearly average from a dozen wells topped the new limits – as much as six times over the limit in one well’s results for PFOS, one of the most studied and common PFAS chemicals.

"We're continuing to pursue an initiative that we began many years ago to add granular activated carbon filtration to all of those wells that have any detections of PFAS chemicals in them," said Bruce Woody, executive director of the authority. "We will get that completed well within the allotted time period."

Recent budget documents from the water system show plans to invest $2 million into a granular activated carbon treatment system at one of its wells. In addition, prior reporting from the Pensacola News Journal, a member of the USA TODAY Network, shows the utility sued manufacturers of firefighting foams , claiming that toxins from the foams seeped into the groundwater around Pensacola’s airport and Naval air station.

Even before the EPA finalized its new limits, the Water Authority of Western Nassau County on Long Island had been installing PFAS treatment on 11 contaminated wells to comply with New York state regulations that went into effect in 2020, according to Superintendent Michael Tierney. Now, with the stricter federal standard, he said there are four additional wells where treatment will need to be installed.

“I've been doing this for 44 years,” Tierney said. “I've never seen a flurry of required regulatory demands such as this.”

The authority is pivoting its efforts to meet not only state-specific standards but also the more stringent federal ones by revisiting and retrofitting previous projects, Tierney added.

“I’m going to have to rip up what I just put in, in many regards,” Tierney said. “So that hurts, that really hurts. If we knew ahead of time and could have planned, it would have been much easier and much more cost-effective.”

As the largest private operator of water services in the U.S., Veolia Water has a few systems where yearly averages topped the new limits, according to USA TODAY’s analysis. EPA data show a water treatment plant at its Delaware location in Wilmington averaged nearly five times over the new limit for PFOA, another of the most studied “forever chemicals.”

The company has been proactive about addressing PFAS in several states for the past few years, and construction is underway for a new treatment facility in Delaware, said Michael Bard, manager of communications and community relations at Veolia North America. The facility will house 42 carbon filters that treat PFAS down to nondetectable levels in a building as large as a regulation-size hockey rink.

The facility is expected to be fully operational by early 2025, and Veolia’s Delaware operations anticipate no challenges in complying with the EPA’s rules by 2029, Bard said.

“Given the regulations, we know that a lot of water systems are probably going to be looking for similar technologies,” Bard said. “We were very proactive in the procurement process and in thinking about supply chains, sourcing and securing those materials.”

The costs associated with the PFAS treatment project will likely be recovered by raising customer rates, Bard said.

“The cost of doing nothing is going to be far worse than the cost of doing something about this,” said Adam Lisberg, senior vice president of communications in Veolia’s municipal water division. “Nobody likes to pay more, but people want to know that they can have confidence in their water.”

Does your water bottle tell you how much to drink? Here's when to obey your thirst instead

Health Does your water bottle tell you how much to drink? Here's when to obey your thirst instead

Woman holding bottle of drink on light blue background, closeup

Do you have a water bottle beside you right now?

Is it etched with words of encouragement, urging you to "keep chugging" because you're "almost there"?

If so, you're not alone. The popularity of reusable water bottles has recently exploded .

It's not just about sustainability anymore. They have become a way to express yourself through colour and design.

And they might even give you a much-needed sense of control.

"The world is very intimidating. There's a lot going on. There's a lot that feels out of our control," University of Queensland marketing expert Ann Wallin says.

"This is something we can measure — how much water we drink."

Dr Wallin says water bottle brands benefit from health advice telling people they should be drinking 2 litres of water a day.

For people who find meeting this recommendation a slog, it's tempting to see a shiny new water bottle as a solution.

But water bottles aside, where do these recommendations even come from, and what happens if you don't meet them?

Why we're told to aim for 2 litres a day

The origin of the 2L-a-day advice is hard to pin down, but similar guidance has been around since at least 1945 .

And there is some rationale behind such recommendations .

In Australia, they're based off the highest median water intake according to the 1995 National Nutrition Survey.

So basically, the recommendation aligns with what many people already drink each day.

For adults, 2–3L is common.

These recommendations apply to all beverages, not just water. Milk, tea, coffee and even alcohol can contribute to total daily intake.

Of course some of those are diuretics, meaning they'll make you urinate more often, so they won't be as hydrating (or healthy) as plain water.

Overall, beverages make up about 75 per cent of your daily fluid intake. The remaining 25 per cent comes from the food you eat.

"We don't tend to think of water as a nutrient, but it's the one nutrient that we are likely to become unwell from the fastest," Monash University sports dietitian Alan McCubbin says.

Water helps carry other nutrients and oxygen to cells, protects organs and tissues, lubricates joints, flushes out toxins and regulates body temperature.

So why does it feel like a slog to drink the recommended 2L a day? Or, for others, like 2L a day is not nearly enough?

"The amount of fluid that we actually need is going to vary quite a bit from person to person," Dr McCubbin says.

Along with age and gender, how active you are, your body composition, if you're pregnant or breastfeeding and where you live can make a difference too.

So if the recommendations don't apply to everyone, how can you be sure you're drinking enough?

Well, our bodies have developed a vital mechanism for that — thirst.

"The body has evolved very strong mechanisms to regulate all of this," Dr McCubbin says.

"In most cases, we can trust those mechanisms."

The science of thirst

If you've ever gone too long without water on a scorching day, you know how powerful thirst can be.

You daydream about a cold bottle of water, or an ice-cold glass with condensation gliding down the side.

(If that made you thirsty, it's time to take a sip from your trusty water bottle.)

A number of things happen when we're running low on water.

"As we lose water, we lose salt as well," Dr McCubbin says.

"But we lose proportionately less salt compared to the water, which means that our blood gets saltier and more concentrated."

Receptors in the brain and carotid arteries, which run either side of your neck, pick up this change.

A hormone is released from the pituitary gland to suppress urine production.

Your blood volume drops, and likely your blood pressure too, triggering another cascade of events.

Your kidneys release the enzyme renin into your bloodstream, which triggers a process that generates the hormone angiotensin II.

Among other effects, angiotensin II alerts the hypothalamus to set off the sensation of thirst.

Once you've gulped down enough water, the concentration of water in your blood increases and your urge to drink settles down.

But it is possible to overcorrect and drink more water than your body needs, which is why Dr McCubbin says it's not necessarily a good idea to down 2L of water in one go.

"You're just going to produce more urine to get rid of what the body perceives as excessive water," he says.

When to go beyond thirst

There are exceptions to the "listen to your thirst" rule.

Young children have an immature thirst mechanism and might not always notice when they're thirsty, while the sensation of thirst can become diminished in older people.

Some medications can act as diuretics, or affect your perception of thirst.

And neurodivergent people can have trouble translating signals their bodies are sending, like thirst, hunger and satiety cues.

Athletes might also need to think beyond thirst, especially when general health isn't their only priority.

"If we're trying to optimise performance, then there may be situations where drinking to thirst is not adequate," Dr McCubbin says.

This is particularly important for athletes involved in longer duration sports in hot and humid environments.

However, over-hydration in athletes is also a concern.

While uncommon in your everyday office worker, drinking too much water is possible, especially in endurance athletes.

It can lead to a potentially fatal disorder called hyponatremia where water dilutes essential sodium levels in your blood.

This is why many athletes will supplement with electrolytes to stay hydrated without throwing off their sodium balance.

Whether you're an Olympian or a regular person trying to do the best for your health, moderation is key.

"For most people, thirst will get them to to where they need to go, and plain water should do the job in 95 per cent of cases," Dr McCubbin says.

"Just make sure there is water available. There might be situations where that does mean carrying around the big water bottle."

At the end of the day, marketing expert Dr Wallin says, there's nothing wrong with having a companion to help you hydrate, as long as you don't fall into the trap of believing you can't trust your thirst response.

"People receive a lot of varying advice, so it can feel as a consumer as though it's quite complex to be healthy," she says.

"I think health and wellness marketing is often really effective when it simplifies that advice."

Listen to Dr Norman Swan and Tegan Taylor discuss the latest hydration craze on RN's What's That Rash? And subscribe to the podcast for more.

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2024 | Impact of Hydrologic Conditions on Soil Microbiome Dynamics

FACULTY SEED GRANT | Global Change Center

A nation-wide investigation of the impact of hydrologic conditions on soil microbiome dynamics, investigators:.

Dr. Jingqiu Liao, Civil and Environmental Engineering
Dr. Durelle Scott, Biological Systems Engineering
Dr. Brian Strahm, Forest Resources and Environmental Conservation
Dr. Amy Pruden, Civil and Environmental Engineering

Climate change has greatly altered the global water cycle, leading to changes in precipitation patterns and soil hydrology. As a key component of terrestrial ecosystems, the soil microbiome stabilizes ecosystems by producing biomass, recycling nutrients, and capturing resources. Studying the interactions between soil microbiomes and hydrological conditions is thus critical to advance knowledge on the impact of climate change on ecosystem resilience and resistance, and to inform strategy development to mitigate its detrimental effect. While climate warming and the concomitant reductions in soil moisture have been widely identified as important environmental stressors that can limit soil microbial diversity, our understanding of how hydrological conditions influence the soil microbiome is still limited.

The goal of this project is to advance the understanding of the influences of hydrologic conditions on soil microbiome dynamics at a nationwide scale. Our major hypothesis is that changes in hydrological conditions alter microbial composition and interspecific interactions and pose heterogeneous selection on the soil microbiome across the United States. We will leverage a unique paired soil microbiome and environmental dataset obtained by the project PI in a recent nationwide soil sampling campaign and employ machine learning and ecological analyses to test our hypothesis. Specifically, we will develop machine learning models to predict microbial diversity with hydrological variables, identify microbial co-occurrence network features associated with hydrological conditions, and assess the influence of hydrological conditions on microbial community assembly. Completion of this project will advance a predictive understanding of large-scale consequences of hydrologic conditions on the soil microbes at a community level. It will also provide fundamental insights into ways to enhance ecosystem resilience and resistance through soil microbiome manipulation in response to climate change.

Each year, the GCC, with funding from the FLSI and the ISCE at Virginia Tech, accepts proposals from GCC faculty to support interdisciplinary research that will lead to collaborative proposals submitted to extramural funding sources. We are seeking projects that link multiple faculty programs and take advantage of unique combinations of expertise at VT, have societal implications and/or a policy component, deal with emerging global change issues that have regional and global significance, and have high potential to eventually leverage external resources.

IMAGES

hypothesis science fair examples testing water
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PPT
Drinking water facts
DEVELOPING A RESEARCH QUESTION AND HYPOTHESIS 1 RESEARCH
Statistics for Water Science Hypothesis Testing Fundamental concepts

VIDEO

Hydrogen water scientific studies

COMMENTS

Hydration for health hypothesis: a narrative review of supporting evidence
Hypothesis. This review advances the hypothesis that optimal water intake positively impacts various aspects of health. We propose an evidence-based definition of optimal hydration as a water intake sufficient to avoid excessive AVP secretion and to ensure a generous excretion of dilute urine, sufficient to avoid chronic or sustained renal water saving.
The Neuroscience of Thirst: How your brain tells you to look for water
Figure 3: Drinking water is rewarding. Researchers in Yuki Oka's group at Caltech conducted a study to see why animals find water rewarding. By using a special kind of sensor that glows in the presence of the rewarding molecule dopamine, they could see what kinds of liquids caused dopamine release. They recorded large spikes of dopamine ...
Narrative Review of Hydration and Selected Health Outcomes in the
1. Introduction. Water is essential for life and is involved in virtually all functions of the human body [].It is important in thermoregulation, as a solvent for biochemical reactions, for maintenance of vascular volume, and as the transport medium for providing nutrients within and removal of waste from the body [].Deficits in body water can compromise our health if they lead to substantial ...
The widespread and unjust drinking water and clean water ...
Using these two measures of poor water quality, we find 2.44% of community water systems, a total of 1165, were Safe Drinking Water Act Serious Violators and 3.37% of Clean Water Act permittees in ...
The impact of water consumption on hydration and cognition among
Increased drinking water quantity may also improve educational outcomes through the effect of hydration on attention, concentration, and short-term memory. ... Our hypothesis was that the majority of students would be dehydrated and that the provision of supplementary water would be associated with improved hydration and improved cognition ...
Hydration for health hypothesis: a narrative review of supporting
Purpose An increasing body of evidence suggests that excreting a generous volume of diluted urine is associated with short- and long-term beneficial health effects, especially for kidney and metabolic function. However, water intake and hydration remain under-investigated and optimal hydration is poorly and inconsistently defined. This review tests the hypothesis that optimal chronic water ...
Science and technology for water purification in the coming decades
The many problems worldwide associated with the lack of clean, fresh water are well known: 1.2 billion people lack access to safe drinking water, 2.6 billion have little or no sanitation, millions ...
A randomized, double-blind water taste test to evaluate the ...
Study design and randomization. A randomized, double-blind water taste test was designed (Fig. 1).Water from a public drinking fountain (tap water) and cold water from a POU water dispenser ...
Drinking water accessibility and quantity in low and middle-income
Drinking water accessibility and quantity in low and middle-income countries: A systematic review. Author links open overlay panel Alexandra Cassivi a, ... The review findings support the hypothesis that the quantity of water available in households is a function of the source location, but the inconsistency in study outcomes highlights the ...
Drinking-water
Microbiologically contaminated drinking water can transmit diseases such as diarrhoea, cholera, dysentery, typhoid and polio and is estimated to cause approximately 505 000 diarrhoeal deaths each year. In 2022, 73% of the global population (6 billion people) used a safely managed drinking-water service - that is, one located on premises ...
Behaviors and Attitudes Associated With Low Drinking Water Intake Among
Drinking water intake did not significantly differ between included and excluded respondents. The percentage of respondents with unknown values or missing data for individual exposure variables ranged from less than 0.1% to 7.0%; we excluded respondents with data missing for a given variable from analyses involving that variable.
Step 2: Formulate a Hypothesis & Make Predictions
Using your recorded observations and information compiled in the first step, the next step is to come up with a testable question. You can use the previously mentioned question (Based on what I know about the pH, DO, temperature and turbidity of my site, is the water of a good enough quality to support aquatic life?) as it relates to the limitations of the World Water Monitoring Day kit, or ...
Why is water important?
Water is also vitally important for regulating body temperature. It has a great capacity to store heat, preventing large, rapid drops in internal temperature, and through sweating, water has ...
Drinking lots of water may seem like a healthy habit
In late 2023, actor Brooke Shields suffered a seizure after "flooding" her body with water. Shields became dangerously low on sodium while preparing for her show by drinking loads of water ...
3. Generate Hypotheses
3. Generate Hypotheses. Developing a hypothesis regarding the cause of the outbreak is often challenging and is a crucial step in the outbreak investigation. Many pathogens that cause waterborne diseases can also be transmitted by contaminated food or by contact with an infected person or animal. When looking for the source of the illness ...
Which Filtration Material Leads to the Best Drinking Water?
Set your timer to 10 minutes and quickly stir each solution with the activated carbon using a clean spoon. After 10 minutes, pour the water and carbon mixture into the filters that you prepared in step 3 of "Preparing Your Samples and Filters," and let the water seep through the filters.
Water
Fun Flavors For Water Water is an excellent calorie-free, sugar-free choice. For some people who are accustomed to drinking sweet beverages, water can initially taste bland. To increase water consumption without losing flavor or to spice up your daily water intake, try these refreshing water-based beverages: Infused water
Bottled water is full of microplastics. Is it still 'natural'?
More recent research has found that typical water bottles have far higher levels: 240,000 particles per liter on average, taking into account smaller fragments known as "nanoplastics.". The ...
Bottled Water: United States Consumers and Their Perceptions of Water
With this part of analysis, we focused on the respondents who used sources other than bottled water for primary drinking purposes but reportedly often used bottled water for drinking. The hypothesis to be tested with this model is the second one, and the independent variable of primary interest is water supply type, which has three categories ...
The impact of water consumption on hydration and cognition among ...
Adequate provision of safe water, basic sanitation, and hygiene (WASH) facilities and behavior change can reduce pupil absence and infectious disease. Increased drinking water quantity may also improve educational outcomes through the effect of hydration on attention, concentration, and short-term memory. A pilot study was conducted to adapt field measures of short-term cognitive performance ...
Impact of Pressure on the Deterioration of Drinking Water ...
Drinking water distribution systems must safely meet the expected demand for water. However, sudden pipe breaks can limit the continuous supply of drinking water. As operating pressure is among the factors affecting the probability of pipe breaks, a methodology was developed in this study to identify the pressure covariates that affect the frequency of water distribution pipe breaks. Five ...
Radium-226-contaminated drinking water: hypothesis on an exposure
The drinking water of these villages partly came from a small river that was contaminated with radium-226 washed out from the dumps of the uranium plant. Only sparse measurements of 226Ra are available, but derived red bone marrow doses for children in the two villages obtained from a simple radio-ecological model show the significance of the ...
Hypothesis
Hypothesis: Based on our prior knowledge of the subject, which is that there are several ways to purify water other than the conventional, $100-dollar Brita filters, such as boiling water, we hypothesize that we will be able to find an efficient method of purifying water. We know, that from our research, filtering water can be done with very ...
Many of America's drinking water systems have a major (PFAS) problem
Hundreds of drinking water systems exceed new PFAS standards. It could grow to thousands. After more than a year of collecting test results for toxic "forever chemicals," the Environmental ...
Water
Groundwater contamination with per- and polyfluoroalkyl compounds (PFASs) has become a growing worldwide environmental issue. The current review comprehensively evaluates the global perspective of PFAS pollution in groundwater. Data from 224 recent research articles covering various land use and source types were reviewed, including industrial facilities, landfills, biosolids applications, and ...
What People Are Getting Wrong This Week: 'Fun' Conspiracy Theories
According to the "phantom time hypothesis," It is not 2024. It is 1727. ... and some believe we don't need water either. ... people still claim that they don't eat or drink for months or years ...
Does your water bottle tell you how much to drink? Here's when to obey
Dr Wallin says water bottle brands benefit from health advice telling people they should be drinking 2 litres of water a day. For people who find meeting this recommendation a slog, it's tempting ...
2024
2015 | Drinking Water 2022 Drought Indicators for Crop Insurance Relief ... Our major hypothesis is that changes in hydrological conditions alter microbial composition and interspecific interactions and pose heterogeneous selection on the soil microbiome across the United States. We will leverage a unique paired soil microbiome and ...
Nearly 2 Million Bottles of Water Has Been Recalled Nationwide
According to a May 23 notice posted by the U.S. Food & Drug Administration (FDA), 1.9 million bottles of Fiji Natural Artesian Water has been recalled. Citing this as a Class III recall, meaning ...

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Bottled Water: United States Consumers and Their Perceptions of Water Quality

Lois Wright Morton

1. Introduction

1.1. Bottled Water vs. Tap Water

1.2. Consumers of Bottled Water

2. Experimental Section

2.2. Methodology

3. Results and Discussion

3.2. Logistic Regression Model 1: Primary Bottled Water Users

3.3. Logistic Regression Model 2: Regular Bottled Water Users

3.4. Discussion

4. Conclusions

Acknowledgments

References and Notes

The impact of water consumption on hydration and cognition among schoolchildren: Methods and results from a crossover trial in rural Mali

Introduction

Materials and methods

School eligibility, school selection, and participant selection

Study design

Measures of hydration

Measures of cognition

Letter cancellation.

Direct image difference.

Indirect image difference.

Forward digit recall.

Reverse digit recall.

Line tracing task.

Data analysis

Univariable analysis