TY - JOUR
T1 - Fluid intake patterns of children and adolescents
T2 - results of six Liq.In7 national cross-sectional surveys
AU - Morin, C.
AU - Gandy, J.
AU - Brazeilles, R.
AU - Moreno, L. A.
AU - Kavouras, S. A.
AU - Martinez, H.
AU - Salas-Salvadó, J.
AU - Bottin, J.
AU - Guelinckx, Isabelle
N1 - Funding Information:
Participant recruitment and data collection in all countries was performed by IPSOS. CM, RB, JB and IG are full-time employees of Danone Research. JS-S, LAM, SAK, JG and HM are members of the advisory board on fluid intake of Danone Research, and have received consultancies from Danone Research. SAK was a scientific consultant for Quest Diagnostics and has active research grants from Danone Research. JS-S and LAM has received consultancies from Danone S.A.
Funding Information:
Danone Research. JS-S, LAM, SAK, JG and HM are members of the advisory board on fluid intake of Danone Research, and have received consultancies from Danone Research. SAK was a scientific consultant for Quest Diagnostics and has active research grants from Danone Research. JS-S and LAM has received consultancies from Danone S.A.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/6/1
Y1 - 2018/6/1
N2 - Purpose: This study aimed to identify and characterize patterns of fluid intake in children and adolescents from six countries: Argentina, Brazil, China, Indonesia, Mexico and Uruguay. Methods: Data on fluid intake volume and type amongst children (4–9 years; N = 1400) and adolescents (10–17 years; N = 1781) were collected using the validated 7-day fluid-specific record (Liq.In7 record). To identify relatively distinct clusters of subjects based on eight fluid types (water, milk and its derivatives, hot beverages, sugar-sweetened beverages (SSB), 100% fruit juices, artificial/non-nutritive sweetened beverages, alcoholic beverages, other beverages), a cluster analysis (partitioning around k-medoids algorithm) was used. Clusters were then characterized according to their socio-demographics and lifestyle indicators. Results: The six interpretable clusters identified 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 six patterns. Conclusions: This analysis showed that consumption of water and SSB were the primary drivers of the clusters. In addition to country, socio-demographic and lifestyle factors played a role in determining the characteristics of each cluster. This information highlights the need to target interventions in particular populations aimed at changing fluid intake behavior and improving health in children and adolescents.
AB - Purpose: This study aimed to identify and characterize patterns of fluid intake in children and adolescents from six countries: Argentina, Brazil, China, Indonesia, Mexico and Uruguay. Methods: Data on fluid intake volume and type amongst children (4–9 years; N = 1400) and adolescents (10–17 years; N = 1781) were collected using the validated 7-day fluid-specific record (Liq.In7 record). To identify relatively distinct clusters of subjects based on eight fluid types (water, milk and its derivatives, hot beverages, sugar-sweetened beverages (SSB), 100% fruit juices, artificial/non-nutritive sweetened beverages, alcoholic beverages, other beverages), a cluster analysis (partitioning around k-medoids algorithm) was used. Clusters were then characterized according to their socio-demographics and lifestyle indicators. Results: The six interpretable clusters identified 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 six patterns. Conclusions: This analysis showed that consumption of water and SSB were the primary drivers of the clusters. In addition to country, socio-demographic and lifestyle factors played a role in determining the characteristics of each cluster. This information highlights the need to target interventions in particular populations aimed at changing fluid intake behavior and improving health in children and adolescents.
KW - Adolescents
KW - Beverages
KW - Children
KW - Clustering analysis
KW - Fluid intake
KW - Hydration
KW - Liq.In
KW - Water
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UR - http://www.scopus.com/inward/citedby.url?scp=85047911619&partnerID=8YFLogxK
U2 - 10.1007/s00394-018-1725-y
DO - 10.1007/s00394-018-1725-y
M3 - Article
C2 - 29858626
AN - SCOPUS:85047911619
SN - 1436-6207
VL - 57
SP - 113
EP - 123
JO - European Journal of Nutrition
JF - European Journal of Nutrition
ER -