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Background: To estimate the economic impact of preventing urinary tract infections (UTI) by increasing water intake among women with recurrent UTI and low fluid intake across seven countries: France, United Kingdom, Spain, United States of America, Mexico, China and Australia. Methods: A Markov model was developed to compare costs and outcomes of UTIs associated with low fluid intake in women versus a strategy of primary prevention by increasing water intake. Model inputs were based on randomized controlled trial data which found that increasing water intake by 1.5 L/day decreased the risk of developing cystitis by 48% in women with low fluid intake and recurrent UTI. A time horizon of 10 years was used; outcomes were from the payer perspective and included both direct and indirect costs, reported in 2019 United States dollars ($). Discounting rates varied by country. Scenarios of increasing levels of compliance to the increased water intake strategy were evaluated. Results: The total cost of one UTI episode, including diagnostics, treatment and complications, ranged from $2164 (Mexico) to $7671 (Australia). Assuming 80% compliance with the increased water intake strategy over a 10-year time horizon, the number of UTIs prevented ranged from 435,845 (Australia) to 24150,272 (China), resulting in total savings of 286 million (Australia) to $4.4 billion (China). Across all countries, increased water intake resulted in lower cost and fewer UTIs compared with low water intake. Conclusion: Preventing recurrent UTIs by increasing water intake would reduce both the clinical and economic burden associated with UTI. Public, healthcare professionals and patients should be made aware about the preventive positive impact of appropriate water intake on UTIs. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that multicomponent interventions may improve meal frequency and eating habits in children, but evidence among young people is limited. This study evaluated the effect of the Healthy High School (HHS) intervention on daily intake of breakfast, lunch, water, fruit, and vegetables at 9-month follow-up. Methods: The study included first-year students (≈16 years) attending high school in Denmark. Participating schools were randomized into the HHS intervention (N = 15) or control group (operating as usual) (N = 15). The intervention was designed to promote well-being (primary outcome) by focusing on healthy habits including meals, stress prevention, and strong peer relations. It included a curriculum, structural and organisational initiatives, a workshop, and a smartphone application. Students completed self-administered online questionnaires at the beginning of the school year and nine months later. To account for clustering of data, we used multilevel logistic regression analyses to estimate odds ratios (OR). We applied an intention-to-treat approach with multiple imputations of missing data. Results: At baseline 4577 of 5201 students answered the questionnaire and 4512 at follow-up. In both groups the proportion of students eating breakfast decreased from approximately 50% to 40% from baseline to follow-up, and lunch frequency decreased from approximately 50% to 47%. Daily water intake, intake of fresh fruit and intake of vegetables remained unchanged from baseline to follow-up. There were no significant between group differences on any of the outcomes at first follow-up: breakfast: OR = 0.85 (95% CI: 0.65;1.10), lunch: OR = 0.96 (95% CI: 0.75;1.22), water intake: OR = 1.14 (95% CI: 0.92;1.40), intake of fresh fruit: (OR = 1.07, 95% CI: 0.84;1.37), vegetables: (OR = 1.01, 95% CI: 0.77;1.33). Conclusion: No evidence of an effect of the HHS intervention was found for any of the outcomes. Future studies are warranted to explore how health promoting interventions can be integrated in further education to support educational goals. Moreover, how to fit interventions to the lives and wishes of young people, by also including systems outside of the school setting. Trial registration: ISRCTN, ISRCTN43284296. Registered 28 April 2017 - retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: Various recommendations exist for total water intake (TWI), yet it is seldom reported in dietary surveys. Few studies have examined how real-life consumption patterns, including beverage type, variety and timing relate to TWI and energy intake (EI). Methods: We analysed weighed dietary records from the National Diet and Nutrition Survey of 1724 British adults aged 19-64 years (2000/2001) to investigate beverage consumption patterns over 24 hrs and 7 days and associations with TWI and EI. TWI was calculated from the nutrient composition of each item of food and drink and compared with reference values. Results: Mean TWI was 2.53 L (SD 0.86) for men and 2.03 L (SD 0.71) for women, close to the European Food Safety Authority "adequate Intake" (AI) of 2.5 L and 2 L, respectively. However, for 33% of men and 23% of women TWI was below AI and TWI:EI ratio was <1 g/kcal. Beverages accounted for 75% of TWI. Beverage variety was correlated with TWI (r 0.34) and more weakly with EI (r 0.16). Beverage consumption peaked at 0800 hrs (mainly hot beverages/ milk) and 2100 hrs (mainly alcohol). Total beverage consumption was higher at weekends, especially among men. Overall, beverages supplied 16% of EI (men 17%, women 14%), alcoholic drinks contributed 9% (men) and 5% (women), milk 5-6%, caloric soft drinks 2%, and fruit juice 1%. In multi-variable regression (adjusted for sex, age, body weight, smoking, dieting, activity level and mis-reporting), replacing 100 g of caloric beverages (milk, fruit juice, caloric soft drinks and alcohol) with 100 g non-caloric drinks (diet soft drinks, hot beverages and water) was associated with a reduction in EI of 15 kcal, or 34 kcal if food energy were unchanged. Using within-person data (deviations from 7-day mean) each 100 g change in caloric beverages was associated with 29 kcal change in EI or 35 kcal if food energy were constant. By comparison the calculated energy content of caloric drinks consumed was 47 kcal/100 g. Conclusions: TWI and beverage consumption are closely related, and some individuals appeared to have low TWI. Energy from beverages may be partly compensated. A better understanding of interactions between drinking and eating habits and their impact on water and energy balance would give a firmer basis to dietary recommendations. [ABSTRACT FROM AUTHOR]