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Evaluating and testing hydration status is increasingly requested by rehabilitation, sport, military and performance-related activities. Besides commonly used biochemical hydration assessment markers within blood and urine, which have their advantages and limitations in collection and evaluating hydration status, there are other potential markers present within saliva, sweat or tear. This literature review focuses on body fluids saliva, sweat and tear compared to blood and urine regarding practicality and hydration status influenced by fluid restriction and/or physical activity. The selected articles included healthy subjects, biochemical hydration assessment markers and a well-described (de)hydration procedure. The included studies (n=16) revealed that the setting and the method of collecting respectively accessing body fluids are particularly important aspects to choose the optimal hydration marker. To obtain a sample of saliva is one of the simplest ways to collect body fluids. During exercise and heat exposures, saliva composition might be an effective index but seems to be highly variable. The collection of sweat is a more extensive and time-consuming technique making it more difficult to evaluate dehydration and to make a statement about the hydration status at a particular time. The collection procedure of tear fluid is easy to access and causes very little discomfort to the subject. Tear osmolarity increases with dehydration in parallel to alterations in plasma osmolality and urine-specific gravity. But at the individual level, its sensitivity has to be further determined.

Micronutrient dilution following sugar-sweetened beverage (SSB) consumption can lead to a qualitative impoverishment of a dietary pattern. The aim of this prospective study was to investigate the relation between SSB consumption and micronutrients. A total 562 adults were tested in 2002 and 2012 for the same anthropometric, lifestyle and nutritional intake activity parameters. Calcium, iron and magnesium intake decreased with increasing baseline SSB intake, and with increasing SSB consumption during the 10 years. A 100 ml increase in SSB consumption was associated with a 22 mg lower intake of calcium, 0.4 mg of iron and 9 mg of magnesium. There was no relation between vitamins and SSB consumption. In conclusion, there was limited evidence in our study, which suggests SSB have minimal dilutional effect on dietary micronutrient consumption. A major limitation of the present study is that of the original 1569 participants in 2002, 36% returned for participation in 2012. ispartof: European Journal of Clinical Nutrition vol:72 issue:1 pages:170-173 ispartof: location:England status: published

BACKGROUND: Regular physical activity ( PA), a high level of fitness and a high diet quality are positively associated with health. However, information about stability of fitness components and diet quality indices is limited. This study aimed to evaluate stability of those parameters. METHODS: This study includes 652 adults (men = 57.56 (10.28) years; women = 55.90 (8.34) years at follow- up) who participated in 2002- 2004 and returned for follow-up at the Policy Research Centre Leuven in 2012-2014. Minutes sport per day and Physical activity level (PAL) were calculated from the Flemish Physical Activity Computerized Questionnaire. Cardiorespiratory fitness (CRF), morphological fitness (MORF; body mass index and waist circumference) and metabolic fitness (METF) (blood cholesterol and triglycerides) were used as fitness components. Diet quality indices (Healthy Eating Index-2010 (HEI), Diet Quality Index (DQI), Mediterranean Diet Score (MDS)) were calculated from a diet record. Tracking coefficients were calculated using Pearson/ Spearman correlation coefficients (gamma(Pearson)) and intra-class correlation coefficients (gamma(ICC)). RESULTS: In both men (gamma(Pearson&ICC) = 0.51) and women (gamma(Pearson) = 0.62 and gamma(ICC) = 0.60) PAL showed good stability, while minutes sport remained stable in women (gamma(Pearson&ICC) = 0.57) but less in men (gamma(Pearson&ICC) = 0.45). Most fitness components remained stable (r >= 0.50) except some METF components in women. In general the diet quality indices and their components were unstable (r < 0.50). CONCLUSIONS: PAL and the majority of the fitness components remained stable, while diet quality was unstable over 10 years. For unstable parameters such as diet quality measurements are needed at both time points in prospective research.