Introduction: Water accounts for about 75% of brain mass. Cognitive performances and mood may be impaired by hypohydration and improved by water supplementation. Two surveys conducted in China demonstrated that a large proportion of adults and children drank less fluid than the amounts recommended by the Chinese Nutrition Society. The association between hypohydration and cognitive performance has not been reported in China. The purpose of this study is to explore the effect of water supplementation on cognitive performances and mood among male college students in Cangzhou, China. Methods and Analysis: A randomized controlled trial is designed to test the hypothesis. A total of 68 male college students aged 18–25 years will be recruited and randomly assigned into water-supplementation group (WS group, n = 34) and no water-supplementation group (NW group, n = 34) after an overnight fasting, i.e., without eating foods and drinking fluid for 12 h. The first morning urine will be collected to determine urine osmolality on the water supplementation day. Cognitive performances and mood will be performed before water supplementation by researchers with questionnaire. Subjects in the WS group will drink 400 mL purified water within 5 min, while those in NW group will not drink any fluid. One hour later, urine will be collected and urine osmolality, cognitive performances and mood will be measured again. Mixed model of repeated measures ANOVA will be used to investigate the effect of water supplementation on cognitive performances. The study would provide information about the benefit of water supplementation on cognitive performances. Ethics and Dissemination: The study protocol is reviewed and approved by the Ethical Review Committee of the Chinese Nutrition Society. Ethical approval project identification code is CNS-2015-001. Results will be published according to the CONSORT statement and will be reported in peer-reviewed journals. Trial registration: Chinese clinical trial registry. Identifier: ChiCTR-IOR-15007020. Registry name “The effect of hydration on cognitive performance”.

The fluid intake and hydration status during pregnancy may influence the health outcomes of both the mother and the fetus. However, there are few studies related to this. The aim of the present study was to investigate fluid intake behaviors among pregnant women in their second trimester, to evaluate their hydration status and pregnancy complications, and to further explore the association of fluid intake and the amniotic fluid index (AFI). Participants’ total fluid intake (TFI) levels were determined using a 7-day 24 h fluid intake questionnaire. The levels of water intake from food were not recorded or measured. Morning urine samples were collected, and both urine osmolality levels and urine specific gravity (USG) were tested to evaluate their hydration status. Fasting blood samples were also collected and measured for osmolality and complete blood count (CBC). A total of 324 participants completed the study. They were divided into four groups based on quartiles of TFI, including participants with lower (LFI1 and LFI2) and higher (HFI1 and HFI2) fluid intake levels. The median TFI was 1485 mL, and the median values of the four groups with different TFI levels were 1348, 1449, 1530, and 1609 mL, respectively. Only 3.4% of the participants attained the recommended value following an adequate water intake (1.7 L) level for pregnant women in China. Plain water was the main TFI resource (78.8~100.00%), and differences in the plain water intake levels among the four groups were evident (χ2 = 222.027, p < 0.05). The urine osmolality decreased sequentially with increasing TFI values from the LFI1 to HFI2 group, and significant differences in the urine osmolality levels among the four groups were evident (p < 0.05). Meanwhile, the percentage of dehydrated participants decreased from 26.8% in the LFI1 group to 0.0% in the HFI2 group (χ2 = 131.241, p < 0.05). Participants with higher TFI values had higher AFI values (χ2 = 58.386, all p < 0.05), and moderate-intensity correlations were found between TFI and urine osmolality, hydration status, and AFI (all p < 0.05). A large proportion of the participants had insufficient TFIs during the second trimester of pregnancy, and a proportion of the participants were dehydrated. The preliminary analysis showed that the AFI was correlated with the TFI during the second trimester of pregnancy. A sufficient TFI is necessary for pregnant women to improve their hydration status and may have effects on their health. The results can provide appropriate scientific references for the development of beneficial recommendations concerning adequate water intake levels for pregnant women in China.

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.

Studies on the water intake of athletes in daily life are insufficient. The objective was to determine the water intake and hydration status among physically active male young adults. In this cross-sectional studies study, 111 physically active male young adults were recruited. The amount of daily total drinking fluid intake (TDF) among participants was recorded and evaluated in real time over 7 days using the “7-day 24-hour fluid intake questionnaire” (liq. In 7). The daily water intake from food (WFF) was calculated using the weighing, duplicate portion, and direct-drying method over 3 days. All urine samples over 3 days were collected, and urine biomarkers were determined. According to 24 h urine osmolality, the participants were divided into three groups with euhydration status, middle hydration, and hypo hydration statuses. Finally, 109 participants completed the study. The median daily total water intake (TWI), TDF, and WFF were 2701, ik1789, and 955 mL, respectively. Among participants, 17 participants (16%) were in euhydration status, 47 participants (43%) were in hypohydration, and 45 participants (41%) were in middle hydration. There were statistical significances in the 24 h urine volume, osmolality, urine specific gravity, and concentrations of K, Na, and Cl in different hydration statuses (χ2 = 28.212, P < 0.01 ; χ2 = 91.341, P < 0.01 ; χ2 = 47.721, P < 0.01 ; χ2 = 41.548, P < 0.01 ; χ2 = 46.863, P < 0.01 ; and χ2 = 40.839, P < 0.01 ). Moderate-intensity correlations were found between the TDF and 24 h urine volume, 24 h urine osmolality, 24 h urine Na concentration, morning urine osmolality, and morning urine Na concentration (r = 0.408, P < 0.01 ; r = -0.378, P < 0.01 ; r = −0.325, P < 0.01 ; r = −0.344, P < 0.01 ; and r = −0.329, P < 0.01 ). There were also moderate-intensity correlations between the TDF and 24 h urine osmolality, morning urine osmolality, and morning urine Na concentration (r = −0.365, P < 0.01 ; r = −0.371, P < 0.01 ; and r = −0.322, P = 0.01 ). Increased and higher moderate-intensity correlations were found between plain water and 24 h urine volume, 24 h urine osmolality, 24 h urine K and Na concentration, morning urine osmolality, and morning urine Na concentration (r = 0.374, P < 0.01 ; r = −0.520, P < 0.01 ; r = −0.312, P < 0.01 ; r = −0.355, P < 0.01 ; r = −0.446, P < 0.01 ; and r = −0.378, P < 0.01 ). Insufficient water intake and hypohydration were common among physically active male young adults. The amount and type of water intake were correlated with hydration status and urine biomarkers. The results could provide scientific and accurate references for the development of recommendations on water intake for athletes.

Background Traditional health management requires many human and material resources and cannot meet the growing needs. Remote medical technology provides an opportunity for health management; however, the research on it is insufficient. Objective The objective of this study was to assess the effects of remote interventions on weight management. Methods In this randomized controlled study, 750 participants were randomly assigned to a remote dietary and physical activity intervention group (group DPI), remote physical activity intervention group (group PI), or control group (group C). At baseline (time 1), day 45 (time 2), and day 90 (time 3), data were collected, including data on dietary intake, physical activity, indexes related to weight control, and health benefits. Results A total of 85.6% (642/750) of participants completed the follow-up. Compared with group C, group DPI showed a significant decrease in energy intake (−581 vs −82 kcal; P<.05), protein intake (−17 vs −3 g; P<.05), fat intake (−8 vs 3 g; P<.05), and carbohydrate intake (−106.5 vs −4.7 g; P<.05) at time 3. Compared with time 1, groups DPI and PI showed a significant decrease in cereal and potato intake (P<.05). Compared with time 1, the physical activity levels related to transportation (group PI: 693 vs 597 metabolic equivalent [MET]–min/week, group C: 693 vs 594 MET-min/week; P<.05) and housework and gardening (group PI: 11 vs 0 MET-min/week, group C: 11 vs 4 MET-min/week; P<.05) in groups PI and C were improved at time 3. Compared with groups PI and C, group DPI showed a significant decrease in weight (−1.56 vs −0.86 kg and −1.56 vs −0.66 kg, respectively; P<.05) and BMI (−0.61 vs −0.33 kg/m2 and −0.61 vs −0.27 kg/m2, respectively; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in body weight (−4.11 vs −1.01 kg and −4.11 vs −0.83 kg, respectively; P<.05) and BMI (−1.61 vs −0.40 kg/m2 and −1.61 vs −0.33 kg/m2, respectively; P<.05) at time 3. Compared with group C, group DPI showed a significant decrease in triglyceride (−0.06 vs 0.32 mmol/L; P<.05) at time 2. Compared with groups PI and C, group DPI showed a significant decrease in systolic blood pressure (−8.15 vs −3.04 mmHg and −8.15 vs −3.80 mmHg, respectively; P<.05), triglyceride (−0.48 vs 0.11 mmol/L and −0.48 vs 0.18 mmol/L, respectively; P<.05), and fasting blood glucose (−0.77 vs 0.43 mmol/L and −0.77 vs 0.14 mmol/L, respectively; P<.05). There were significant differences in high-density lipoprotein cholesterol (−0.00 vs −0.07 mmol/L; P<.05) and hemoglobin A1c (−0.19% vs −0.07%; P<.05) between groups DPI and C. Conclusions Remote dietary and physical activity interventions can improve dietary intake among participants with overweight and obesity, are beneficial for weight control, and have potential health benefits. Trial Registration Chinese Clinical Trial Registry ChiCTR1900023355; https://www.chictr.org.cn/showproj.html?proj=38976