Drinking patterns and hydration biomarkers among young adults with different levels of habitual total drinking fluids intake in Baoding, Hebei Province, China: a cross-sectional study

Seasonality Affects Fluid Intake Behaviors among Young Adults in Hebei, China

BACKGROUND

Evidence on the association between environmental factors and fluid intake behavior remains limited. The current study aims to explore seasonal variations in fluid intake behaviors among young adults in China.

METHODS

A prospective cohort of 79 healthy young adults (43 males and 36 females) aged 19-21 in Hebei, China, was assessed for fluid intake behaviors for four seasons. For each assessment, the participants' anthropometric measurements were collected. Temperature and humidity on survey days were measured. Participants' total drinking fluid (TDF) was recorded using a self-administrative 7 d, 24 h fluid intake questionnaire. To calculate water from food (WFF), we weighed all foods consumed by participants. Duplicates of consumed food samples were collected to measure the water content via the drying method.

RESULTS

The mean total water intake (TWI) was 2761 ± 881, 2551 ± 845, 2210 ± 551, and 1989 ± 579 for spring, summer, fall, and winter, respectively (F(2.37) = 42.29, p < 0.001). The volume and proportion of TWI from TDF and WFF varied across the four seasons. The volume of WFF in spring (1361 ± 281, F(2.61) = 17.21, p < 0.001) and TDF in summer (1218 ± 502, F(2.62) = 9.36, p < 0.001) was among the highest, while participants' fluid intake behaviors in spring and summer were less distinct than the other pairwise comparisons. A moderate association was found between outdoor temperature and TDF (r = 0.53, p < 0.01). Different general estimating equations suggested that gender, seasonality, outdoor temperature, differences in indoor and outdoor temperature, and mean temperature were independent factors of TDF. An interactive effect was found for gender and temperature, showing that the expected TDF of males may increase more as the temperature climbs.

CONCLUSIONS

Gender, seasonality, and air temperature could significantly affect fluid intake behaviors, including the amount and type of fluid intake. However, the independent effect of BMI and humidity remains unclear.

A Study of the Fluid Intake, Hydration Status, and Health Effects among Pregnant Women in Their Second Trimester in China: A Cross-Sectional Study

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.

Habitual Total Drinking Fluid Intake Did Not Affect Plasma Hydration Biomarkers among Young Male Athletes in Beijing, China: A Cross-Sectional Study

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.

Seasonal effects on urinary iodine concentrations in women of reproductive age: An observational study in Tanzania and South Africa

BACKGROUND

Iodine intake in populations is usually assessed by measuring urinary iodine concentrations (UICs) in spot samples. Hot climate conditions may reduce urine volume, thus leading to overestimations of UIC and thereby masking inadequate iodine intake.

OBJECTIVES

We investigated the effects of season on UICs in 2 populations exposed to high-temperature climates.

METHODS

In this observational study, we examined women (18-49 years) in Tanzania (ncold = 206; nhot = 179) and South Africa (ncold = 157; nhot = 126) during cold and hot seasons. From each woman in both seasons, we obtained two 24-hour urine collections and 2 spot urine samples, as well as salt, water, and cow's milk samples. We measured the urine volume, UIC, and urinary creatinine concentration (UCC). The 24-hour urinary iodine excretion (UIE) was calculated and used to estimate the iodine intake. We used linear mixed-effects models to test for differences between seasons.

RESULTS

In Tanzanian women, we observed no seasonal effect on the urine volume, 24-hour UIE, 24-hour UIC, spot UIC, spot UIC:UCC ratio, or salt iodine concentration. In South African women, the median 24-hour urine volume was 1.40 L (IQR, 0.96-2.05 L) in the winter and 15% lower in the summer (P < 0.001). The median 24-hour UIE was 184 µg/day (IQR, 109-267 µg/day) in the winter and 34% lower in the summer (P < 0.001), indicating a lower iodine intake. As a result, UICs did not significantly differ between seasons in 24-hour collections and spot samples, whereas the spot UIC:UCC ratio differed by 21% (P < 0.001) and reflected the lower iodine intake. In both study populations, the within- and between-person variabilities in urine volume, 24-hour UICs, and spot UICs were higher than the variability between seasons.

CONCLUSIONS

Spot UIC may slightly overestimate the iodine intake in hot temperatures due to concentrated urine, and methods to correct for urine volume may be considered. Local seasonal differences in iodine intakes may also occur in some populations. This trial was registered at http://www.clinicaltrials.gov as NCT03215680.

Young Adults with Higher Salt Intake Have Inferior Hydration Status: A Cross-Sectional Study

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.

The Relationships between Water Intake and Hydration Biomarkers and the Applications for Assessing Adequate Total Water Intake among Young Adults in Hebei, China

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.

Effects of Water Restriction and Supplementation on Cognitive Performances and Mood among Young Adults in Baoding, China: A Randomized Controlled Trial (RCT)

The brain is approximately 75% water. Therefore, insufficient water intake may affect the cognitive performance of humans. The present study aimed to investigate the effects of water restriction and supplementation on cognitive performances and mood, and the optimum amount of water to alleviate the detrimental effects of dehydration, among young adults. A randomized controlled trial was conducted with 76 young, healthy adults aged 18–23 years old from Baoding, China. After fasting overnight for 12 h, at 8:00 a.m. of day 2, the osmolality of the first morning urine and blood, cognitive performance, and mood were measured as a baseline test. After water restriction for 24 h, at 8:00 a.m. of day 3, the same indexes were measured as a dehydration test. Participants were randomly assigned into four groups: water supplementation group (WS group) 1, 2, or 3 (given 1000, 500, or 200 mL purified water), and the no water supplementation group (NW group). Furthermore, participants were instructed to drink all the water within 10 min. Ninety minutes later, the same measurements were performed as a rehydration test. Compared with the baseline test, participants were all in dehydration and their scores on the portrait memory test, vigor, and self-esteem decreased (34 vs. 27, p < 0.001; 11.8 vs. 9.2, p < 0.001; 7.8 vs. 6.4, p < 0.001). Fatigue and TMD (total mood disturbance) increased (3.6 vs. 4.8, p = 0.004; 95.7 vs. 101.8, p < 0.001) in the dehydration test. Significant interactions between time and volume were found in hydration status, fatigue, vigor, TMD, symbol search test, and operation span test (F = 6.302, p = 0.001; F = 3.118, p = 0.029; F = 2.849, p = 0.043; F = 2.859, p = 0.043; F = 3.463, p = 0.021) when comparing the rehydration and dehydration test. Furthermore, the hydration status was better in WS group 1 compared to WS group 2; the fatigue and TMD scores decreased, and the symbol search test and operation span test scores increased, only in WS group 1 and WS group 2 (p < 0.05). There was no significant difference between them (p > 0.05). Dehydration impaired episodic memory and mood. Water supplementation improved processing speed, working memory, and mood, and 1000 mL was the optimum volume.