Water accounts for 75% of brain mass. Associations may exist between hydration and cognitive performance. The objective of this study was to investigate the effects of dehydration and rehydration on cognitive performance and mood. In this self-control trial, 12 men were recruited from a medical college in Cangzhou, China. After 12 h of overnight fasting, the participants took baseline tests at 8:00 AM on day 2. First morning urine and blood osmolality were analyzed to determine hydration state. Height, weight, and blood pressure were measured following standardized procedures. A visual analog scale for the subjective sensation of thirst was applied, and a profile of mood states questionnaire was applied. Tests were conducted for cognitive performance, including a test of digit span forward and backward, digit-symbol substitutions, dose-work, and stroop effects. Participants were required not to drink water for 36 h but were given three meals on day 3. On day 4, the same indexes were tested as a baseline test. At 8:30 AM, participants drank 1500 mL of purified water over 15 min. After a 1 h interval, the same measurements were performed. Compared with baseline test results, during the dehydration test, participants had lower scores of vigor (11.9 vs. 8.8, %, p = 0.007) and esteem-related affect (8.2 vs. 5.7, %, p = 0.006), lower total scores of digit span (14.3 vs. 13.3, %, p = 0.004), and higher error rates for dose-work (0.01 vs. 0.16, %, p = 0.005). Compared with the dehydration test scores, rehydration test scores showed that fatigue (4.3 vs. 2.1, %, p = 0.005) and total mood disturbance (TMD) (99.0 vs. 90.2, %, p = 0.008) improved, and scores of forward, backward, and total digit span increased (7.7 vs. 8.6, p = 0.014; 5.7 vs. 1.2, p = 0.019; 13.3 vs. 15.4, p = 0.001). Increases were also noted in correct number of digit symbol substitutions, reading speed, and mental work ability (70.8 vs. 75.4, p < 0.001; 339.3 vs. 486.4, n/min, p < 0.001; 356.1 vs. 450.2, p < 0.001), and reaction time decreased (30.2 vs. 28.7, s, p = 0.002). As a conclusion, dehydration had negative effects on vigor, esteem-related affect, short-term memory, and attention. Rehydration after water supplementation alleviated fatigue and improved TMD, short-term memory, attention, and reaction.

The objectives of this study were to assess the associations between fluid intake and urine biomarkers and to determine daily total fluid intake for assessing hydration status for male college students. A total of 68 male college students aged 18–25 years recruited from Cangzhou, China completed a 7-day cross-sectional study. From day 1 to day 7; all subjects were asked to complete a self-administered 7-day 24-h fluid intake record. The foods eaten by subjects were weighed and 24-h urine was collected for three consecutive days on the last three consecutive days. On the sixth day, urine osmolality, specific gravity (USG), pH, and concentrations of potassium, sodium, and chloride was determined. Subjects were divided into optimal hydration, middle hydration, and hypohydration groups according to their 24-h urine osmolality. Strong relationships were found between daily total fluid intake and 24-h urine biomarkers, especially for 24-h urine volume (r = 0.76; p < 0.0001) and osmolality (r = 0.76; p < 0.0001). The percentage of the variances in daily total fluid intake (R²) explained by PLS (partial least squares) model with seven urinary biomarkers was 68.9%; two urine biomarkers—24-h urine volume and osmolality—were identified as possible key predictors. The daily total fluid intake for assessing optimal hydration was 2582 mL, while the daily total fluid intake for assessing hypohydration was 2502 mL. Differences in fluid intake and urine biomarkers were found among male college students with different hydration status. A strong relationship existed between urine biomarkers and fluid intake. A PLS model identified that key variables for assessing daily total fluid intake were 24-h urine volume and osmolality. It was feasibility to use total fluid intake to judge hydration status.

The mass concentration of microplastics in stools and influencing factors remain unclear. The aim was to investigate the types and mass concentrations of microplastics in the stools of young college students and to explore potential influencing factors. Twenty-six participants were recruited from colleges in each city using stratified simple sampling, including Changsha, Shanghai, and Changchun. Participants' dietary and fluid intake behavior was recorded using the 3-day 24-h dietary questionnaire and the 7-day 24-h fluid intake record, respectively. Lifestyle factor information related to microplastic exposure was collected through a microplastic exposure questionnaire. Stools were collected and detected using pyrolysis gas chromatography-mass spectrometry (Py-GCMS) method. Eventually, 78 participants completed the study. The detection rate of microplastics, including polyethylene (PE), polyvinyl chloride (PVC), polystyrene (PS), polypropylene (PP) and polyethylene terephthalate (PET), in stools was 98.7%, with a total mass concentration of 54.7 (10.1-102.7) μg/g. There were differences in the total mass concentrations of microplastics in the stools of participants in three cities, namely Changsha, Shanghai, and Changchun, which decreased sequentially (χ² = 47.819, P < 0.05). Participants with a relatively high frequency of takeaway food consumption had higher total mass concentrations of microplastics mass concentrations in stools (χ² = 7.390, P < 0.05). Participants with a relatively high frequency of consuming reheated food had a greater mass concentration of PET microplastics (χ² = 6.117, P < 0.05). The total mass concentration of microplastics, as well as the mass concentrations of PE, PVC, PP, and PA66, in the bottled water intake group were greater than those in the nonintake group (all P < 0.05). Overall, the total mass concentration of microplastics in stools was related to residential city, consumption of reheated food, and bottled water intake (all P < 0.05). Young college students generally experience microplastic exposure, with the main types being PE, PVC, PS, PP, PET, and PA66. Living location, reheated food consumption, and bottled water intake were factors influencing microplastic exposure.

This study aimed to systematically assess the total environmental exposure to microplastics and determine the internal exposure levels in the human body. A total of 26 young college students were recruited. Exposure scenario estimation methods were used to establish evaluation models. The dietary and water intake behaviors of the participants were documented with questionnaires. The food and water consumed by the participants were sampled using weight and duplicate meal methods. Furthermore, air samples from the activity regions of the participants were collected. Fasting serum, 24-h urine, and fecal samples were also collected. Pyrolysis gas chromatography/mass spectrometry (Py-GCMS) helped identify the types and determine mass concentrations of microplastics across all samples, and the internal and external exposure levels of microplastics among the population were further evaluated. Microplastics were frequently observed in food samples, with mass concentrations ranging from 2.50 to 91.30 μg/g. Water samples also contained microplastics, with concentrations ranging from 0.02 to 18.41 μg/g. Indoor and outdoor air contained PS, PE, PP, PVC, and PET. The exposure levels of young college students in Changsha to microplastics through dietary intake, water intake, and inhalation were quantified at 346.65 μg/kg bw/d, 41.17 μg/kg bw/d, and 59.57 μg/kg bw/d, respectively. Cumulatively, the total exposure to microplastics from these three sources was 460.20 μg/kg bw/d. Median microplastic levels in serum and feces samples were 20.81 μg/g and 97.36 μg/g, respectively. Additionally, urine samples indicated the presence of seven types of microplastics (PS, PE, PP, PVC, PET, PA66, and PMMA), with a median exposure level of 5.06 μg/g. Among young college students in Changsha, the primary microplastic exposure source was dietary intake, followed by air and drinking water. The internal exposure level in serum was higher than that in urine.

Background: Water requirements increases with gestational age. Insufficient water intake causes dehydration, which may adversely affect maternal health and birth outcomes. However, few related studies have been conducted. The purposes are to assess the water intake and hydration state among pregnant women, and to investigate the associations with pregnancy complications and maternal and infant outcomes. Methods: A prospective observational cohort study will be applied. A total of 380 pregnant women will be recruited from the First Affiliated Hospital of Hainan Medical University. Hydration biomarkers and health outcomes will be tested during 15~17 weeks’ gestation, 20~22 weeks’ gestation, 30~32 weeks’ gestation, during childbirth and 42 days after childbirth. Daily fluid intake will be collected using a 24-h fluid intake record for 7 consecutive days. A semi-quantified food frequency method will be used to assess food intake and water intake from food. Anthropometric measurement will be taken following standardized processes. Intracellular fluid (ICF) and extracellular fluid (ECF) will be measured using a body composition analyzer. Morning fasting urine and blood osmolality will be tested by laboratory physicians using an osmotic pressure molar concentration meter. Pregnancy complications will be assessed and diagnosed throughout pregnancy and childbirth. Maternal-infant outcomes will be monitored using related indicators and technologies. In order to explore the internal mechanism and interactions from the perspective of endocrine, pregnancy related hormones (estradiol, prolactin, progesterone) and the hydration-related hormones (copeptin) will be tested during pregnancy. A mixed model of repeated measures ANOVA will be analyzed using SAS 9.2. Results: The results may provide basic data on water intake among pregnant women. The association between hydration state and maternal-infant outcomes will also be explored. Conclusions: This preliminary exploratory study findings will fill the gaps in the research on water intake, hydration and maternal health, birth outcomes, provide scientific reference data for updating recommendation on water adequate intake among pregnant women, and provide suggestion for developing water intake interventions. Trial registration: The protocol has been registered on the website of Chinese Clinical Trial Registry. The Identifier code is ChiCTR1800019284. The Registry date is 3 November, 2018. Registry name is “Study for the correlation between hydration state and pregnancy complications, maternal and infant outcomes during pregnancy”.

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