Adequate water intake and optimal hydration status during pregnancy are crucial for maternal and infant health. However, research on water intake by pregnant women in China is very limited. This study mainly aimed to observe the daily total water intake (TWI) of pregnant women and its different sources and to investigate the relationship between their water intake and hydration biomarkers. From October to November 2020, a convenience sample of pregnant women in the second trimester (n = 21) was recruited. Under conditions close to daily life, they undertook a 3-day metabolic trial. Each participant was provided with sufficient bottled water, and the weight of what they drank each time was measured. The intake of other beverages and foods was measured using a combination of weighing and duplicate portion method. Fasting venous blood and 24 h urine samples were collected and analyzed for the hydration biomarkers, including the serum/urine osmolality, urine pH, urine specific gravity, and the concentrations of major electrolytes in urine and serum. The results showed that the mean daily TWI was 3151 mL, of which water from beverages and foods accounted for 60.1% and 39.9%, respectively. The mean total fluid intake (TFI) was 1970 mL, with plain water being the primary contributor (68.7%, r = 0.896). Among the participants, 66.7% (n = 14, Group 1) met the TWI recommendation set by the Chinese Nutrition Society. Further analysis revealed that the TFI, water from beverages and foods, plain water, and milk and milk derivatives (MMDs) were significantly higher in Group 1 than those who did not reach the adequate intake value (Group 2) (p < 0.05). The results of hydration biomarkers showed that the mean 24 h urine volume in Group 1 was significantly higher than that in Group 2 (p < 0.05), while the 24 h urine osmolality, sodium, magnesium, phosphorus, chloride, and creatinine concentrations in Group 1 were significantly lower than those in Group 2 (p < 0.05). However, no significant differences were observed in serum biomarkers. Partial correlation analysis showed that TWI was moderately positively correlated with 24 h urine volume (r = 0.675) and negatively correlated with urine osmolality, sodium, potassium, magnesium, calcium, phosphorus, and chloride concentrations (r = from-0.505 to -0.769), but it was not significantly correlated with serum biomarkers. Therefore, under free-living conditions, increasing the daily intake of plain water and MMDs is beneficial for pregnant women to maintain optimal hydration. The hydration biomarkers in urine are more accurate indicators of water intake and exhibit greater sensitivity compared to serum biomarkers. These findings provide a scientific basis for establishing appropriate water intake and hydration status for pregnant women in China.

The purposes of this study were to explore the drinking patterns, and urinary and plasma hydration biomarkers of young adults with different levels of habitual total drinking fluid intake. A cross-sectional study was conducted among 111 young male athletes in Beijing, China. Total drinking fluids and water from food were assessed by a 7-day, 24-h fluid intake questionnaire and the duplicate portion method, respectively. The osmolality and electrolyte concentrations of the 24-h urine and fasting blood samples were tested. Differences in groups LD1 (low drinker), LD2, HD1, and HD2 (high drinker), divided according to the quartiles of total drinking fluids, were compared using one-way ANOVA, Kruskal−Wallis H-tests, and chi-squared tests. A total of 109 subjects completed the study. The HD2 group had greater amounts of TWI (total water intake) and higher and lower contributions of total drinking fluids and water from food to TWI, respectively, than the LD1, LD2, and HD1 groups (p < 0.05), but the amounts of water from food did not differ significantly among the four groups (all p > 0.05). Participants in the HD2 group had higher amounts of water than participants in the LD1, LD2, and HD1 groups (p < 0.05); SSBs were the second top contributor of total drinking fluids, ranging from 24.0% to 31.8%. The percentage of subjects in optimal hydration status increased from 11.8% in the LD1 group to 58.8% in the HD2 group (p < 0.05). The HD2 and HD1 groups had 212−227 higher volumes of urine than the LD1 and LD2 groups (p < 0.05). No significant differences were found in the plasma biomarkers (p > 0.05), with the exception of higher concentrations of K in the HD1 group than in the LD1 group (p < 0.05). Subjects with higher amounts of total drinking fluids had better hydration status than those with lower total drinking fluids, but not better drinking patterns. Habitual total drinking fluids did not affect the plasma biomarkers.

The body\'s water and sodium balances are tightly regulated and monitored by the brain. Few studies have explored the relationship between water and salt intake, and whether sodium intake with different levels of fluid intake leads to changes in hydration status remains unknown. The aim of the present study was to determine the patterns of water intake and hydration status among young adults with different levels of daily salt intakes. Participants\' total drinking fluids and water from food were determined by a 7-day 24-h fluid intake questionnaire for 7 days (from Day 1 to Day 7) and duplicate portion method (Day 5, Day 6 and Day 7). Urine of 24 h for 3 days (Day 5, Day 6 and Day 7) was collected and tested for the osmolality, the urine-specific gravity (USG), the concentrations of electrolytes, pH, creatinine, uric acid and the urea. The fasting blood samples for 1 day (Day 6) were collected and measured for the osmolality and the concentrations of electrolytes. The salt intakes of the participants were evaluated from the concentrations of Na of 24 h urine of 3 days (Day 5, Day 6 and Day 7). Participants were divided into four groups according to the quartile of salt intake, including the low salt intake (LS1), LS2, high salt intake (HS1) and HS2 groups. In total, 156 participants (including 80 male and 76 female young adults) completed the study. The salt intakes were 7.6, 10.9, 14.7 and 22.4 g among participants in the four groups (LS1, LS2, HS1 and HS2 groups, respectively), which differed significantly in all groups (F = 252.020; all p < 0.05). Compared to the LS1 and LS2 groups, the HS2 group had 310-381, 250-358 and 382-655 mL more amounts of water from the total water intake (TWI), total drinking fluids and water from food (all p < 0.05), respectively. Participants in the HS2 group had 384-403, 129-228 and 81-114 mL more in the water, water from dishes and staple foods, respectively, than those in the groups of LS1 and LS2 (p < 0.05). The HS2 group excreted 386-793 mL more urine than those in the groups of LS1 and LS2 (p < 0.05). However, regarding urine osmolality, the percentage of participants with optimal hydration status decreased from 41.0% in LS1 and LS2 to 25.6% in the HS2 group (p < 0.05). Participants with higher salt intake had higher TWI, total drinking fluids and water from food. Nevertheless, they had inferior hydration status. A reduction in salt intake should be encouraged among young adults to maintain optimal hydration status.

Water is an essential nutrient for humans. A cross-sectional study was conducted among 159 young adults aged 18-23 years in Hebei, China. The total drinking fluids and water from food were obtained by 7-day 24 h fluid intake questionnaires and the duplicate portion method, respectively. Pearson\'s correlation coefficients were performed to determine the relationship between fluid intake and 24 h urinary biomarkers and plasma biomarkers. A multivariable partial least squares (PLS) model was used to identify the key predictors in modeling the total water intake (TWI) with 24 h urine biomarkers. Logistic regressions of the TWI against binary variables were performed, and the receiver operating characteristic curve (ROC) was analyzed to determine the cutoff value of the TWI for the optimal hydration status and dehydration without adjustments to favor either the sensitivity or specificity. In total, 156 participants (80 males and 76 females) completed the study. Strong relationships were found between the total drinking fluids, TWI, and 24 h urine biomarkers among young adults, especially for the 24 h urine volume (r = 0.784, p < 0.001; r = 0.747, p < 0.001) and osmolality (r = -0.589, p < 0.001; r = -0.477, p < 0.001), respectively. As for the FMU and plasma biomarkers, no strong relationships were found. The percentages of the variance in TWI explained by the PLS model with 13 urinary biomarkers were 66.9%. The optimal TWI values for assessing the optimal hydration and dehydration were 2892 mL and 2482 mL for young males, respectively, and 2139 mL and 1507 mL for young females, respectively. Strong relationships were found between the TWI, total drinking fluids, and 24 h urine biomarkers, but not with the FMU and plasma biomarkers, among young adults, including males and females. The 24 h urine biomarkers were more sensitive than the first morning urinary biomarkers in reflecting the fluid intake. The TWI was a reliable index for assessing the hydration statuses for young adults in free-living conditions.

BACKGROUND: Water is essential for maintaining the functions of human body properly. Studies have shown that the amounts and contributions of fluids were associated with health and hydration status. The objectives of the study was that to explore the differences of water intake pattern and hydration biomarkers among young males and females in different hydration statuses.
METHODS: A cross-sectional study was implemented among 159 young adults aged 18-23 years in Hebei, China. The total drinking fluids and water from food were obtained by 7-day 24-h fluid intake questionnaire and duplicate portion method, respectively. The osmolality and electrolyte concentrations of the 24 h urine and plasma were tested. Differences in optimal hydration (OH), middle hydration (MH) and hypohydration (HH) groups, divided by the osmolality of 24 h urine, were compared.
RESULTS: Totally, 156 participants (80 males and 76 females) completed the study. OH group had highest proportions of participants met the recommendations of total water intake (TWI) and total drinking fluids of China (34.5%, 36.2%), while HH group had lowest (7.7%, 0.0%). OH group had higher amounts of TWI, total drinking fluids, water and lower amounts of sugar-sweetened-beverages (SSBs) (P < 0.05). The percentage of total drinking fluids in TWI decreased from 54.1% in OH group to 42.6% in HH group (P < 0.05). OH group had higher and lower contributions of water and SSBs to total drinking fluids (P < 0.05); produced 551-950 mL more, excreted significantly less quantity of solutes of urine (P < 0.05). No significant differences were found in plasma osmolality among the three groups (P > 0.05). Among both males and females, the amounts of TWI and water were higher in OH group than others (P < 0.05). Males had 4.3% lower, 5.4% and 1.1% higher contributions of milk and milk products, SSBs and alcohol to total drinking fluids than females (P < 0.05); males had higher volume of urine than females only in MH group (P < 0.05). There were no significant differences of plasma osmolality between males and females in the same group (P > 0.05).
CONCLUSIONS: Young adults with optimal hydration status had better water intake pattern and less concentrated urine. Females maybe have better water intake pattern than males. Trial registration Chinese clinical trial registry. Name of the registry: Relationship of drinking water and urination.
BACKGROUND: ChiCTR-ROC-17010320. Date of registration: 01/04/2017. URL of trial registry record: http://www.chictr.org.cn/edit.aspx?pid=17601&htm=4 .

BACKGROUND: The purposes were to investigate the drinking patterns and hydration biomarkers among young adults with different levels of habitual total drinking fluids intake.
METHODS: A cross-sectional study was conducted among 159 young adults aged 18-23 years in Baoding, China. Total drinking fluids and water from food were assessed by 7-day 24-h fluid intake questionnaire and duplicate portion method, respectively. The osmolality and electrolyte concentrations of the 24 h urine and fasting blood samples were tested. Differences in LD1 (low drinker), LD2, LD3 and HD (high drinker) groups, stratified according to the quartiles of total drinking fluids, were compared using one-way ANOVA, Kruskal-Wallis H test and chi-square test.
RESULTS: A total of 156 participants (80 males and 76 females) completed the study. HD group had greater amounts of TWI (Total Water Intake), water from food, higher and lower contributions of total drinking fluids and water from food to TWI, respectively, than LD1, LD2 and LD3 groups (p < 0.05). Participants in HD group had higher amounts of water and water from dishes than participants in LD1, LD2 and LD3 groups (p < 0.05). No significant differences were found in the contributions of different fluids to total drinking fluids within the four groups (p > 0.05). The osmolality of urine was 59-143 mOsm/kg higher in LD1 than that in LD2, LD3 and HD group (p < 0.05). The percentage of participants in optimal hydration status increased from 12.8% in LD1 group to 56.4% in HD group (p < 0.05). HD and LD3 groups had 386~793 higher volumes of urine than that of LD1 and LD2 groups (p < 0.05). Differences were found in the concentrations of electrolytes among the four groups (p < 0.05). No significant differences were found in the plasma biomarkers (p > 0.05), with the exception of higher concentration of Mg in LD3 and HD groups than that in LD1 and LD2 groups (p < 0.05).
CONCLUSIONS: Participants with higher total drinking fluids had better drinking pattern and hydration status. Interventions should be undertaken to advise adults to have adequate total drinking fluids, in order to keep in optimal hydration status.
BACKGROUND: The registration number was ChiCTR-ROC-17010320, which was registered on the Chinese clinical trial registry.

OBJECTIVE: Urine colour (U Col) is simple to measure, differs between low-volume and high-volume drinkers, and is responsive to changes in daily total fluid intake (TFI). However, to date, no study has quantified the relationship between a change in TFI and the resultant change in U Col. This analysis aimed to determine the change in TFI needed to adjust 24-h U Col by 2 shades on an 8-colour scale, and to evaluate whether starting U Col altered the relationship between the change in TFI and change in U Col.
METHODS: We performed a pooled analysis on data from 238 healthy American and European adults (50 % male; age, 28 (sd 6) years; BMI 22.9 (sd 2.6) kg/m(2)), and evaluated the change in TFI, urine volume (U Vol), and specific gravity (U SG) associated with a change in U Col of 2 shades.
RESULTS: The mean [95 % CI] change in TFI and U Vol associated with a decrease in U Col by 2 shades (lighter) was 1110 [914;1306] and 1011 [851;1172] mL/day, respectively, while increasing U Col by 2 shades (darker) required a reduction in TFI and U Vol of -1114 [-885;-1343] and -977 [-787;-1166] mL/day. The change in U Col was accompanied by changes in U SG (lighter urine: -.008 [-.007;-.010]; darker urine: +.008 [.006;.009]). Starting U Col did not significantly impact the TFI change required to modify U Col by 2 shades.
CONCLUSIONS: Our results suggest a quantifiable relationship between a change in daily TFI and the resultant change in U Col, providing individuals with a practical means for evaluating and adjusting hydration behaviours.