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Nutrition Today:
doi: 10.1097/NT.0b013e31829787b2
Feature Article

Short-term Physiological Effects of Increased Water Intake in a Clinical Setting

Perrier, Erica PhD; Klein, Alexis PhD

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Author Information

Erica Perrier, PhD, is a hydration and physiology scientist, Danone Research, Centre Daniel Carasso, Palaiseau, France.

Alexis Klein, PhD, is a hydration and physiology senior manager, Danone Research, Centre Daniel Carasso, Palaiseau, France.

This study was conducted at Forenap, Rouffach, France, and was funded by Danone Research. The authors are employees of Danone Research. E.P. was involved in the statistical analysis of the data, drafted the manuscript, and presented these data at the H4H conference. A.K. was involved in planning and carrying out the study, reviewing the statistical analysis, and editing the manuscript.

Correspondence: Erica Perrier, PhD, RD128, 91767 Palaiseau Cedex, France ( erica.perrier@danone.com).

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Abstract

Low water intake is associated with long-term adverse health outcomes. Despite this, few studies had examined hydration physiology in the general population, where adequate intake, and not excessive loss, is the primary determinant of hydration. This study sought to evaluate the responsiveness of hydration biomarkers in urine and blood to acute changes in water intake. Key findings were that markers of urine concentration and urine volume change rapidly in response to a change in water intake, whereas plasma osmolality is maintained. Moreover, urine concentration varies as a function of the time of day, with nighttime and morning urine samples being more concentrated than afternoon samples. These results suggest that short, well-timed urine samples, such as those taken in the afternoon, may provide values comparable with 24-hour collections, which are more time-consuming and less convenient.

Water is an essential nutrient, comprising 55% to 60% of total body mass and 73% of lean mass.1 Hydration physiology has been extensively studied in situations of acute water loss, such as prolonged exercise or heat exposure. It is well documented that a net loss of total body water due to sweat as well as insufficient water replacement during sport reduces exercise performance and alters thermoregulatory capacity.2–4 However, until recently, few studies had examined hydration physiology in the general population, where habitual water intake, and not excessive water loss, is the primary determinant of hydration. Recent evidence suggests that habitual low fluid intake is linked to health outcomes such as increased long-term risk of chronic kidney disease,5 kidney stones,6–8 and possibly even new-onset hyperglycemia.9 Thus, the ability to track water intake and hydration is of potential interest to the general population as well as to clinicians and other healthcare practitioners.

The ability to track changes in hydration biomarkers due to water intake is challenging because water turnover occurs constantly, and body water moves within and between intracellular and extracellular compartments. Proposed biomarkers of hydration status include measures of plasma and urine osmolality, as well as other associated urinary measures such as specific gravity, color, and volume. However, no single biomarker of hydration has yet been shown to be adapted to all situations.10 Recently, we published a study11 demonstrating significant differences in 24-hour urine variables between those who consume low (≤1.2 L/d of total water) versus high (≥2.0 L/d) daily fluid volumes, with low drinkers producing a significantly smaller volume of urine with a correspondingly higher urine osmolality, specific gravity, and darker color compared with high drinkers. Moreover, although plasma osmolality (POsm) has been demonstrated to track acute dehydration,12 we found no differences in POsm in average adults who were not subjected to exercise or heat exposure. This suggests the possibility of adaptive mechanisms to conserve total body water and, therefore, maintain POsm despite low fluid intake. A cascade of regulatory hormones, including arginine vasopressin, regulate total body water by modulating water reabsorption and excretion via the kidneys. Indeed, we observed increased circulating arginine vasopressin in the low drinkers in this study, supporting the hypothesis that habitual low fluid consumption may lead to a state of sustained antidiuresis. Urinary parameters therefore appeared well adapted to distinguish between habitual low and high drinkers in normal daily conditions. However, the “gold standard” of 24-hour urine collection is certainly impractical for widespread use. Shorter duration sampling would be more convenient and less costly, but the possible circadian fluctuation of urine concentration has not been well described. To address these challenges, we recently completed a study that sought to evaluate the responsiveness of hydration biomarkers in urine and blood to acute changes in water intake, as well as to assess diurnal variation of hydration biomarkers in urine.

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METHODS

Fifty-two participants (age, 24.8 ± 3.1 years; body mass index, 22.4 ± 1.6 kg/m2) were included and classified based on self-reported habitual fluid intake over 3 consecutive weekdays (30 low drinkers and 22 high drinkers). They then completed a 5-day inpatient parallel group crossover intervention. During the first 2 days of the inpatient intervention (baseline), participants followed a fluid regimen quantitatively comparable with their self-reported intake habits (1.0 L/d for low and 2.5 L/d for high drinkers). In the 3 days immediately after baseline, fluid intakes between groups were reversed (crossover). After the 5 days of inpatient intervention, the low group was encouraged to maintain an increased water intake for 1 month, after which they returned for a second 24-hour inpatient visit (follow-up). During all inpatient visits, the timing and volume of water ingested were carefully controlled and distributed throughout waking hours (from 7:00 am to 11:00 pm), and standardized meals were provided to ensure consistent dietary solute load. Each day during the inpatient portions of the study, POsm was sampled twice daily (morning and evening). All urine produced over each 24-hour period was collected in 5 separate containers, corresponding to morning (AM; 07:00 am–12:00 noon), early afternoon (PM1; 12:00 noon–4:00 pm), late afternoon (PM2; 4:00–8:00 pm), evening (EVE; 8:00–11:00 pm), and overnight (NIGHT; 11:00 pm–7:00 am) collections. Urine collections were analyzed for osmolality (UOsm), specific gravity (USG), color (UCol), and volume (UVol). Following these measures, each of the 5 samples representing a 24-hour period was combined and measures were repeated on each complete 24-hour urine collection.

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RESULTS

Fluid Intake

Daily fluid intake during the screening period was 0.71 ± 0.28 and 2.66 ± 0.66 L/d for low and high drinkers, respectively. During the inpatient intervention, water intake was fixed at either 1.0 or 2.5 L/d, depending on group assignment and study phase (baseline or crossover). During the 1 month after the inpatient screening, low drinkers consumed 1.86 ± 0.50 L/d of total fluids (Figure 1).

FIGURE 1.
FIGURE 1.
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Baseline Analyses: Group Differences and Circadian Variation in Hydration Biomarkers
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Plasma Osmolality

Plasma osmolality was not different between am or pm assessments or between groups (mean [95% CI], low drinkers: am, 291 [290, 293] mOsm/kg; pm, 290 [289, 293] mOsm/kg; high drinkers: am, 288 [285, 290] mOsm/kg; pm, 289 [286, 291] mOsm/kg; P = .78).

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24-Hour Urine Biomarkers

At baseline, low drinkers produced (mean [95% CI]) 1.05 [0.92–1.19] L/24 hours of urine, with mean 24-hour UOsm that exceeded the criterion for euhydration in athletic adults13 (UOsm, 764 [707–820] mOsm/kg; USG, 1.020 [1.019–1.021]; UCol, 5.2 [4.8–5.6]), and were significantly different from high drinkers (UVol, 2.44 [2.32–2.57] L/24 hours; UOsm, 332 [276–389] mOsm/kg; USG, 1.010 [1.009–1.011]; UCol, 2.6 [2.2–2.9]; all P < .001).

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Circadian Variation in Urine Biomarkers

In both low and high drinkers, the time of collection significantly influenced urinary biomarkers (Figure 2). In low drinkers, AM and NIGHT samples were significantly (P < .05) more concentrated than PM samples for UOsm, USG, and UCol. In high drinkers, AM and NIGHT samples had lower UVol and higher UOsm, USG, and UCol (P ≤ .01) than PM samples did. The short samples showed satisfactory correlations with the 24-hour sample (r2 for UOsm: 0.69 to 0.78), with the values obtained from the PM1 and PM2 samples being most similar, on average, to the 24-hour value.

FIGURE 2.
FIGURE 2.
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Crossover Analyses: Effect of a Change in Water Intake on Hydration Biomarkers
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Low Drinkers: Effect of an Increased Daily Water Intake (+1.5 L/d)

In comparison with measures obtained at baseline, POsm did not change in response to an increase in water intake (crossover, mean [95% CI]: am, 291 [289, 293] mOsm/kg; pm, 291 [289, 293] mOsm/kg; P = .82). All urine parameters responded significantly to a change in water intake (Figure 3): UVol increased significantly (2.38 [2.24, 2.52] L/24 hours; P < .001), whereas measures representing urine concentration decreased (UOsm, 352 [308, 397] mOsm/kg, P< .001; USG, 1.010 [1.008, 1.011], P < .001]; UCol, 2.7 [2.3, 3.0]).

FIGURE 3.
FIGURE 3.
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High: Effect of a Decreased Daily Water Intake (−1.5 L/d)

Changes in high drinkers mirrored the changes seen in low drinkers. Compared with baseline values, POsm did not change (mean [95% CI]: am, 290 [288, 293] mOsm/kg; pm, 290 [287, 292] mOsm/kg; P = .16). UVol decreased significantly (1.11 [0.98, 1.24] L/24 hours, P < .001), whereas urine concentration increased (UOsm, 720 [675, 765] mOsm/kg, P < .001; USG, 1.019 [1.018, 1.020], P < .001; UCol, 4.8 [4.5, 5.1], P < .001).

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Follow-up Analysis (Low Drinkers Only): Effect of 1-Month Increased Water Intake on Biomarkers

During the 1-month follow-up, low drinkers increased their total fluid intake to 1.86 ± 0.50 L/d, representing an average increase of 1.1 L/d. During the inpatient follow-up visit, POsm was maintained (mean [95% CI]: am, 288 [285, 291] mOsm/kg; pm, 291 [290, 292] mOsm/kg), and all urinary parameters were similar to those of the inpatient crossover period (UOsm, 380 [351, 409] mOsm/kg; USG, 1.011 [1.010, 1.012]; UCol, 3.7 [3.6, 3.8]).

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DISCUSSION

The key finding of this study suggests that urinary hydration biomarkers are responsive to changes in water intake and that urine volume and concentration respond within 24 hours of initiating a change in daily intake. Urinary biomarkers such as osmolality, specific gravity, and color appear to be particularly well suited to track subtle changes in hydration in response to day-to-day changes in fluid intake volume. In contrast, plasma osmolality is tightly regulated and maintained across a broad range of daily fluid intake volumes.14 This distinction is important because plasma osmolality is widely regarded as a responsive biomarker to hypohydration due to sweating.12,15 Our findings contrast those of normal adults in sedentary conditions with the previously studied athletic populations and suggest that different biomarkers are relevant in different situations.

In sedentary individuals who do not lose excessive amounts of water to sweat, the relationship between fluid intake and urinary output is largely controlled by regulating antidiuretic activity in the kidneys. In situations of low fluid intake volume, increased antidiuresis minimizes the volume of water lost in urine, whereas excess water is eliminated via diuresis. Thus, urine concentration and volume have the ability to provide insight into the hormonal regulation of body water without the need to assess hormone concentrations directly. Given the recently identified links between fluid intake, urine output, and chronic kidney disease,5,16 there is at least epidemiological evidence that chronic antidiuretic activity as evidenced by low water intake or low urine output may worsen the rate of glomerular decline. Thus, biomarkers of urine concentration have potential applicability in the screening of and primary prevention for long-term kidney pathology.

Moreover, a limiting factor in the inclusion of hydration in common health assessments has historically been the need to collect full 24-hour urine samples to accurately measure 24-hour urine concentration. These results provide at least preliminary evidence that shorter, well-timed collections, such as those obtained over a 3- to 5-hour period, may be sufficient to approximate 24-hour urine concentration. These short collections may provide similar information with considerably less effort on the part of patients, healthcare practitioners, or the general population interested in monitoring urine concentration as a measure of adequate fluid intake. In conclusion, short, well-timed collections have the potential to reflect 24-hour fluid intakes as efficiently as 24-hour urine collections, but with a better practicality. Urinary biomarkers in short collections therefore have the potential to advance the use of hydration assessment as a routine component in primary prevention, particularly of chronic kidney disease, which currently represents a major healthcare burden at the worldwide level.

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REFERENCES

1. Peronnet F, Mignault D, du Souich P, et al. Pharmacokinetic analysis of absorption, distribution and disappearance of ingested water labeled with D(2)O in humans. Eur J Appl Physiol. 2012; 112: 2213–2222.

2. Sawka MN, Montain SJ, Latzka WA. Hydration effects on thermoregulation and performance in the heat. Comp Biochem Physiol A Mol Integr Physiol. 2001; 128: 679–690.

3. Nielsen B. Temperature regulation; effects of sweat loss during prolonged exercise. Acta Physiol Scand Suppl. 1986; 556: 105–109.

4. Lopez RM, Casa DJ, Jensen KA, et al. Examining the influence of hydration status on physiological responses and running speed during trail running in the heat with controlled exercise intensity. J Strength Cond Res. 2011; 25: 2944–2954.

5. Strippoli GF, Craig JC, Rochtchina E, Flood VM, Wang JJ, Mitchell P. Fluid and nutrient intake and risk of chronic kidney disease. Nephrology. 2011; 16: 326–334.

6. Curhan GC, Willett WC, Knight EL, Stampfer MJ. Dietary factors and the risk of incident kidney stones in younger women: Nurses’ Health Study II. Arch Intern Med. 2004; 164: 885–891.

7. Dai M, Zhao A, Liu A, You L, Wang P. Dietary factors and risk of kidney stone: a case-control study in Southern China. J Ren Nutr. 2013; 23: 21–28

.


8. Sorensen MD, Kahn AJ, Reiner AP, et al. Impact of nutritional factors on incident kidney stone formation: a report from the WHI OS. J Urol. 2012; 187: 1645–1649.

9. Roussel R, Fezeu L, Bouby N, et al. Low water intake and risk for new-onset hyperglycemia. Diabetes Care. 2011; 34: 2551–2554.

10. Armstrong LE. Assessing hydration status: the elusive gold standard. J Am Coll Nutr. 2007; 26: 575S–584S.

11. Perrier E, Vergne S, Klein A, et al. Hydration biomarkers in free-living adults with different levels of habitual fluid consumption. Br J Nutr. 2013; 109: 1678–1687.

12. Cheuvront SN, Ely BR, Kenefick RW, Sawka MN. Biological variation and diagnostic accuracy of dehydration assessment markers. Am J Clin Nutr. 2010; 92: 565–573.

13. Sawka MN, Burke LM, Eichner ER, Maughan RJ, Montain SJ, Stachenfeld NS. American College of Sports Medicine position stand. Exercise and fluid replacement. Med Sci Sports Exerc. 2007; 39: 377–390.

14. IOM. Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate. Washington, DC: National Academies Press; 2004; .

15. Cheuvront SN, Fraser CG, Kenefick RW, Ely BR, Sawka MN. Reference change values for monitoring dehydration. Clin Chem Lab Med. 2011; 49: 1033–1037.

16. Clark WF, Sontrop JM, Macnab JJ, et al. Urine volume and change in estimated GFR in a community-based cohort study. Clin J Am Soc Nephrol. 2011; 6: 2634–2641.

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