Finnish Children Healthy Eating Index (FCHEI) and its associations with family and child characteristics in pre-school children

Abstract

Objective: The objective was to develop a Finnish Children Healthy Eating Index (FCHEI), to determine the relative validity of the index and to examine associations between the index and familial sociodemographic and lifestyle characteristics. Design: Cross-sectional samples of children participating in a population-based birth cohort study in Finland. Setting: Type I Diabetes Prediction and Prevention (DIPP) Study cohort. Subjects: Three-day food records from 1-year-old (n 455), 3-year-old (n 471) and 6-year-old (n 713) children were completed between 2003 and 2005. Results: Validity of the FCHEI was assessed by studying the associations between the FCHEI and nutrient intakes of the children. Among all age groups, intakes of SFA and sugars decreased across increasing quartiles of the FCHEI while intakes of PUFA, dietary fibre, vitamin D and vitamin E increased. Among 3-and 6-yearolds, being cared for at home was associated with the lowest FCHEI quartile (diet that deviates most from the recommendations). The lowest FCHEI quartile was also associated with residence in a semi-urban area among the 3-year-olds and low maternal education and smoking during pregnancy among the 6-year-olds. Conclusions: The FCHEI serves as a valid indicator of the quality of Finnish children's diet. Public health programmes aimed at improving the dietary behaviours of pre-school aged children should aim to improve the quality of food served at home. Families with history of lower parental education, maternal smoking during pregnancy or non-urban place of residence may require special attention.

Parental health behaviour predictors of childhood and adolescent dietary trajectories

“…Like previous studies, we show that maternal diet (7,12,13) , but not physical exercise (14) , is associated with early childhood diet, and we confirm univariable associations of maternal smoking with unhealthier diets (11) and of maternal non-smoking with healthier diets (7,10) . However, our multivariable findings differ from previous studies indicating that parental alcohol consumption and smoking predict child diet (6)(7)(8)(9)(10)(11) . Ref.…”

“…Compared with previous research (7)(8)(9)(11)(12)(13)(14) , our study provides a broader view over a longer time horizon of how multiple health behaviours from both parents are associated with dietary trajectories throughout childhood and adolescence. Like previous studies, we show that maternal diet (7,12,13) , but not physical exercise (14) , is associated with early childhood diet, and we confirm univariable associations of maternal smoking with unhealthier diets (11) and of maternal non-smoking with healthier diets (7,10) .…”

Development of a Dietary Index to Assess Overall Diet Quality for Chinese School-Aged Children: The Chinese Children Dietary Index

“…The Chinese Children Dietary Index score was observed to be related not only to the foods/food groups and nutrients incorporated into the index, but also to other essential nutrients, such as protein, calcium, magnesium, potassium, vitamin C, vitamin E, and riboflavin. These correlation coefficients were consistent with diet indices developed for children in western countries 8,16,24 and in Indian girls who were vegetarian. 33 These results revealed that the Chinese Children Dietary Index can be used as a valuable SSB¼sugar-sweetened beverage.…”

“…Germany (0 to 17 years), [19][20][21][22][23] Finland (1 to 6 years), 24 Spain (2 to 24 years), [25][26][27] and Canada (older than 3 years). 28,29 A few dietary indices measured diet quality among children in Asian countries.…”

Children skilled in mental abacus show enhanced non-symbolic number sense

“…To examine if there is substantial group difference between children skilled in mental abacus and their peers on non-symbolic number sense, some important cognitive factors would be controlled. The factors included general intelligence (Cowan & Powell, 2014;Fuchs, Fuchs, Compton, Hamlett, & Wang, 2015;Jordan et al, 2013), visuospatial processing ability (Boonen, van Wesel, Jolles, & van der Schoot, 2014;Kyttala et al, 2014;Looi et al, 2017;Swanson, Jerman, & Zheng, 2009), processing speed (Berg, 2008;Bull & Johnston, 1997;Fuchs et al, 2006), and language processing (Hecht, Torgesen, Wagner, & Rashotte, 2001;Purpura & Ganley, 2014;Wei, Yuan, Chen, & Zhou, 2012). It is to ensure that group difference in approximate number sense originates from mental abacus experience rather than outperformances of the cognitive factors.…”