What Characterizes Fluid Intake Patterns across the World?

• Published in: Annals of nutrition and metabolism Vol. 77; no. Suppl 4; pp. 12 - 14
• Main Authors: Morin, Clémentine, Gandy, Joan, Moreno, Luis A., Kavouras, Stavros A., Martinez, Homero, Salas-Salvado, Jordi, Bottin, Jeanne
• Format: Journal Article
• Language: English
• Published: Basel, Switzerland 01.02.2022
• Subjects: Abstracts; Cluster analysis; Beverages intake; Drinking patterns; Children; Hydration
• ISSN: 0250-6807; 1421-9697; 1421-9697
• DOI: 10.1159/000520480

Introduction: Total fluid intake and the type of fluids consumed have been reported by many studies [<xref ref-type="bibr" rid="ref1">1 -<xref ref-type="bibr" rid="ref3">3 ] and have shown that while an individual may be drinking sufficiently, in terms of volume, to meet or exceed recommendations on fluid intake, there may be a wide variety of combinations of fluids within that total volume [<xref ref-type="bibr" rid="ref4">4 -<xref ref-type="bibr" rid="ref6">6 ]. Moreover, considering only volume and fluid types may limit the interpretation of the data [<xref ref-type="bibr" rid="ref7">7 ]. In a novel approach, we propose to analyze and understand fluid intake patterns as opposed to only fluid volume or types. The primary aim of this study was to identify patterns of fluid intake in children and adolescents from 6 countries: Argentina, Brazil, Mexico, Uruguay, China, and Indonesia. The secondary aim was to characterize those fluid intake patterns. Methods: A validated 7-day fluid specific record (Liq.In7 record) [<xref ref-type="bibr" rid="ref8">8 ] was used to collect primary data on fluid intake amongst children and adolescents (10–17 years; N = 1,781). To identify relatively distinct clusters of subjects based on 8 fluid types (water, milk and its derivatives, hot beverages, sugar-sweetened beverages [SSB], 100% fruit juices, artificial/nonnutritive sweetened beverages, alcoholic beverages, and other beverages), a cluster analysis (partitioning around k-medoids algorithm) was used. Clusters were then characterized according to their socio-demographic and lifestyle indicators. Results: The 6 clusters identified (Fig. 1) were low drinkers – SSB (n = 523), low drinkers – water and milk (n = 615), medium mixed drinkers (n = 914), high drinkers – SSB (n = 513), high drinkers – water (n = 352), and very high drinkers – water (n = 264). Country of residence was the dominant characteristic, followed by socioeconomic level, in all 6 patterns. Conclusion: Fluid intake patterns among children are primarily driven by water and SSB. In addition to country, socio-demographic and lifestyle factors determined the characteristics of each cluster. Therefore, interventions aiming to encourage healthier fluid intake behavior need to target and be tailored to a particular subpopulation.