BACKGROUND: Social inequalities in bodyweight start early in life and track into adulthood. Dietary patterns are an important determinant of weight development in children, towards both overweight and underweight. Therefore, we aimed to examine weight development between age 5 and 10 years by ethnicity, SES and thereafter by BMI category at age 5, to explore its association with dietary patterns at age 5.METHODS: Participants were 1765 children from the Amsterdam Born Children and their Development (ABCD) cohort that had valid data on BMI at age 5 and 10 and diet at age 5. Linear mixed model analysis was used to examine weight development between age 5 and 10 years and to assess if four previously identified dietary patterns at age 5 (snacking, full-fat, meat and healthy) were associated with weight development. Analyses were adjusted for relevant confounders, stratified by ethnicity and SES and thereafter stratified per BMI category at age 5.RESULTS: Overall, weight decreased in Dutch and high SES children and increased in non-Dutch and low/middle SES children. Across the range of bodyweight categories at age 5, we observed a conversion to normal weight, which was stronger in Dutch and high SES children but less pronounced in non-Dutch and low/middle SES children. Overall, the observed associations between weight development and dietary patterns were mixed with some unexpected findings: a healthy dietary pattern was positively associated with weight development in most groups, regardless of ethnicity and SES (e.g. Dutch B 0.084, 95% CI 0.038;0.130 and high SES B 0.096, 95% CI 0.047;0.143) whereas the full-fat pattern was negatively associated with weight development (e.g. Dutch B -0.069, 95% CI -0.114;-0.024 and high SES B -0.072, 95% CI -0.119;-0.026).CONCLUSIONS: We observed differential weight development per ethnic and SES group. Our results indicate that each ethnic and SES group follows its own path of weight development. Associations between dietary patterns and weight development showed some unexpected findings; follow-up research is needed to understand the association between dietary patterns and weight development.
This study was motivated by a desire to help working-age individuals gain a better understanding of their daily nutritional intakes with a new self-reported dietary assessment method because an unhealthy eating behavior increases the risks of developing chronic diseases. In this study, we present the design and evaluation of NutriColoring, a food diary that leverages doodling on sketches to report and reflect on everyday diet in the working context. Through a 2-week field study involving 18 participants, the usefulness of NutriColoring in facilitating dietary assessment was tested by making comparisons with the typical bullet diary method. Our quantitative results showed that NutriColoring provided users with improved dietary assessment experience and intrinsic motivations, with significantly low task frustration and high enjoyment. Because of the freedom and playfulness in reporting intakes at work, the interview findings showed a high acceptance of employing NutriColoring at work. This article is concluded with a set of implications for the design and development of a Doodling toolkit to support healthy eating behaviors among office workers.
Background: Our aim was to identify dietary patterns by the level of maternal education that contribute to BMI, fat mass index (FMI), and fat-free mass index (FFMI) in children at age 5 and to assess if these dietary patterns are related to BMI at age 10. Methods: Per group (low/middle/high level), Reduced Rank Regression (RRR) was used to derive dietary patterns for the response variables BMI z-score, FMI, and FFMI in 1728 children at age 5 in the Amsterdam Born Children and their Development (ABCD) cohort. Regression analyses were then used to determine the association with BMI at age 10. Results: In each group, pattern 1 was characterized by its own cluster of food groups. Low: water/tea, savory snacks, sugar, low-fat meat, and fruits; middle: water/tea, low-fat cheese, fish, low-fat dairy, fruit drink, low-fat meat, and eggs; and high: low-fat cheese, fruits, whole-grain breakfast products, and low-fat and processed meat. Additionally, in each group, pattern 1 was positively associated with BMI z-scores at age 10 (low: β ≤ 0.43 [95% CI ≤ 0.21; 0.66], p < 0.001, middle: β ≤ 0.23 [0.09; 0.36], p ≤ 0.001, and high: β ≤ 0.24 [0.18; 0.30], p < 0.001). Conclusions: The dietary patterns stratified by the level of maternal education are characterized by different food groups. But in all the groups, pattern 1 is positively associated with BMI at age 10.
MULTIFILE
