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Background: Cognitive impairment is projected to affect a preponderant proportion of the aging population. Lifelong dietary habits have been hypothesized to play a role in preventing cognitive decline. Among the most studied dietary components, fish consumptionhas been extensively studied for its potential effects on the human brain. Aims: To perform a meta-analysis of observational studies exploring the association between fish intake and cognitive impairment/decline and all types of dementia. Methods: A systematic search of electronic databases was performed to identify observational studies providing quantitative data on fish consumption and outcomes of interest. Random effects models for meta-analyses using only extreme exposure categories, subgroup analyses, and dose-response analyses were performed to estimate cumulative risk ratios (RRs) and 95% confidence intervals (CIs). Results: The meta-analysis comprised 35 studies. Individuals reporting the highest vs. the lowest fish consumption were associated with a lower likelihood of cognitive impairment/decline (RR = 0.82, 95% CI: 0.75, 0.90, I2 = 61.1%), dementia (RR = 0.82, 95% CI: 0.73, 0.93, I2 = 38.7%), and Alzheimer's disease (RR = 0.80, 95% CI: 0.67, 0.96, I2 = 20.3%). The dose-response relation revealed a significantly decreased risk of cognitive impairment/decline and all cognitive outcomes across higher levels of fish intake up to 30% for 150 g/d (RR = 0.70, 95% CI: 0.52, 0.95). The results of this relation based on APOE ε4 allele status was mixed based on the outcome investigated. Conclusions: Current findings suggest fish consumption is associated with a lower risk of cognitive impairment/decline in a dose-response manner, while for dementia and Alzheimer's disease there is a need for further studies to improve the strength of evidence. [ABSTRACT FROM AUTHOR]

Growing evidence suggests that sustained concentrated urine contributes to chronic metabolic and kidney diseases. Recent results indicate that a daily urinary concentration of 500 mOsm/kg reflects optimal hydration. This study aims at providing personalized advice for daily water intake considering personal intrinsic (age, sex, height, weight) and extrinsic (food and fluid intakes) characteristics to achieve a target urine osmolality (UOsm) of 500 mOsm/kg using machine learning and optimization algorithms. Data from clinical trials on hydration (four randomized and three non-randomized trials) were analyzed. Several machine learning methods were tested to predict UOsm. The predictive performance of the developed algorithm was evaluated against current dietary guidelines. Features linked to urine production and fluid consumption were listed among the most important features with relative importance values ranging from 0.10 to 0.95. XGBoost appeared the most performing approach (Mean Absolute Error (MAE) = 124.99) to predict UOsm. The developed algorithm exhibited the highest overall correct classification rate (85.5%) versus that of dietary guidelines (77.8%). This machine learning application provides personalized advice for daily water intake to achieve optimal hydration and may be considered as a primary prevention tool to counteract the increased incidence of chronic metabolic and kidney diseases. [ABSTRACT FROM AUTHOR]

Elevated copeptin, a surrogate marker of vasopressin, is linked to low water intake and increased diabetes risk. Water supplementation in habitual low-drinkers with high copeptin significantly lowers both fasting plasma (fp) copeptin and glucose. This study aims at investigating possible underlying mechanisms. Thirty-one healthy adults with high copeptin (> 10.7 pmol·L−1 (men), > 6.1 pmol−1 (women)) and 24-h urine volume of < 1.5L and osmolality of > 600 mOsm·kg−1 were included. The intervention consisted of addition of 1.5 L water daily for 6 weeks. Fp-adrenocorticotropic hormone (ACTH), fp-cortisol, 24-h urine cortisol, fasting and 2 h (post oral glucose) insulin and glucagon were not significantly affected by the water intervention. However, decreased (Δ baseline-6 weeks) fp-copeptin was significantly associated with Δfp-ACTH (r = 0.76, p < 0.001) and Δfp-glucagon (r = 0.39, p = 0.03), respectively. When dividing our participants according to baseline copeptin, median fp-ACTH was reduced from 13.0 (interquartile range 9.2–34.5) to 7.7 (5.3–9.9) pmol L−1, p = 0.007 in the top tertile of copeptin, while no reduction was observed in the other tertiles. The glucose lowering effect from water may partly be attributable to decreased activity in the hypothalamic–pituitary–adrenal axis. ClinicalTrials.gov: NCT03574688. [ABSTRACT FROM AUTHOR]

Purpose: Growing evidence suggests hydration plays a role in metabolic dysfunction, however data in humans are scarce. This study examined the cross-sectional association between hydration and metabolic dysfunction in a representative sample of the US population. Methods: Data from 3961 adult NHANES (National Health and Nutrition Examination Survey) participants (49.8% female; age 46.3 ± 0.5 years) were grouped by quartile of urine specific gravity (USG, 2007–2008 cohort) or urine osmolality (UOsm, 2009–2010 cohort) as measures of hydration. Metabolic dysfunction was assessed by glycemic and insulinemic endpoints and by components of the metabolic syndrome. Multivariate-adjusted linear and logistic regression models were used. Results: Increasing quartiles of USG but not UOsm was associated with higher fasting plasma glucose (FPG), glycated hemoglobin (all P < 0.01), HOMA-IR and elevated insulin (all P < 0.05). Compared with the lowest quartile, those with the highest USG but not UOsm had greater risk of metabolic syndrome (Q4 vs. Q1, OR (99% CI): 1.6 (1.0, 2.7), P = 0.01) and diabetes (Q4 vs. Q1, OR: 1.8 (1.0, 3.4), P < 0.05). Additionally, those with USG > 1.013 or UOsm > 500 mOsm/kg, common cut-off values for optimal hydration based on retrospective analyses of existing data, had less favorable metabolic markers. In a subset of participants free from diabetes mellitus, impaired kidney function, hypertension and diuretic medication, USG remained positively associated with FPG (P < 0.01) and elevated FPG (P < 0.05). Conclusion: These analyses provide population-based evidence that USG as a proxy for hydration is associated with glucose homeostasis in NHANES 2007–2008. The same association was not significant when UOsm was used as a proxy for hydration in the 2009–2010 wave. Clinical trial registry: Not applicable, as this was a reanalysis of existing NHANES data. [ABSTRACT FROM AUTHOR]

Purpose: An increasing body of evidence suggests that excreting a generous volume of diluted urine is associated with short- and long-term beneficial health effects, especially for kidney and metabolic function. However, water intake and hydration remain under-investigated and optimal hydration is poorly and inconsistently defined. This review tests the hypothesis that optimal chronic water intake positively impacts various aspects of health and proposes an evidence-based definition of optimal hydration. Methods: Search strategy included PubMed and Google Scholar using relevant keywords for each health outcome, complemented by manual search of article reference lists and the expertise of relevant practitioners for each area studied. Results: The available literature suggest the effects of increased water intake on health may be direct, due to increased urine flow or urine dilution, or indirect, mediated by a reduction in osmotically -stimulated vasopressin (AVP). Urine flow affects the formation of kidney stones and recurrence of urinary tract infection, while increased circulating AVP is implicated in metabolic disease, chronic kidney disease, and autosomal dominant polycystic kidney disease. Conclusion: In order to ensure optimal hydration, it is proposed that optimal total water intake should approach 2.5 to 3.5 L day−1 to allow for the daily excretion of 2 to 3 L of dilute (< 500 mOsm kg−1) urine. Simple urinary markers of hydration such as urine color or void frequency may be used to monitor and adjust intake. [ABSTRACT FROM AUTHOR]

Purpose: This investigation had three purposes: (a) to evaluate changes in hydration biomarkers in response to a graded rehydration intervention (GRHI) following 3 days of water restriction (WR), (b) assess within-day variation in urine concentrations, and (c) quantify the volume of fluid needed to return to euhydration as demonstrated by change in Ucol. Methods: 115 adult males and females were observed during 1 week of habitual fluid intake, 3 days of fluid restriction (1000 mL day−1), and a fourth day in which the sample was randomized into five different GRHI groups: no additional water, CON; additional 500 mL, G+0.50; additional 1000 mL, G+1.00; additional 1500 mL, G+1.50; additional 2250 mL, G+2.25. All urine was collected on 1 day of the baseline week, during the final 2 days of the WR, and during the day of GRHI, and evaluated for urine osmolality, color, and specific gravity. Results: Following the GRHI, only G+1.50 and G+2.25 resulted in all urinary values being significantly different from CON. The mean volume of water increase was significantly greater for those whose Ucol changed from > 4 to < 4 (+ 1435 ± 812 mL) than those whose Ucol remained ≥ 4 (+ 667 ± 722 mL, p < 0.001). Conclusions: An additional 500 mL of water is not sufficient, while approximately 1500 mL of additional water (for a total intake between 2990 and 3515 mL day−1) is required to return to a urine color associated with adequate water intake, following 3 days of WR. [ABSTRACT FROM AUTHOR]

The purpose of measurement standardization is to achieve closer comparability of results obtained using different commercial systems. Regarding serum protein immunoassays, a reference preparation (BCR-470) was released in 1993 and adopted by manufacturers across the world to value-assign their assay calibrators for routine methods to reduce method-dependent variation. Moving from nephelometric (Beckman Immage 800) to turbidimetric determination (Roche Cobas c 501) of seven serum proteins, we preliminarily checked the comparability of results between the two systems. The study was performed according to the CLSI EP9-A protocol on 30 fresh sera, tested on each system in duplicate, and subdivided on two different days, without recalibration and using manufacturers’ control materials to validate the runs. Both manufacturers’ package inserts provide statements that kit calibrators are traceable to BCR-470. Suggested reference intervals are also the same. Although a fairly good correlation was observed ( r = 0.955), the comparison of ceruloplasmin methods produced evidence of highly significant proportional (regression slope, 0.572) and constant bias (intercept, 0.05 g/L). Absolute and percentage mean differences were −0.11 g/L (95% confidence interval (CI) −0.13 to −0.10 g/L) and −39.1% (CI −43.1 to −35.2%), respectively. No other evaluated proteins showed similar problems. Lacking a ceruloplasmin reference method, it is impossible to demonstrate that one of the two assays produces true ceruloplasmin values. The problem is, however, that results coming from the two assays are clearly not comparable. This may be either due to a lack of commutability of the reference material with biological samples in the evaluated assays or to calibration problems by manufacturers in one of the stages of the calibration hierarchy. [ABSTRACT FROM AUTHOR]