Data-Driven Dietary Patterns, Nutrient Intake and Body Weight Status in a Cross-Section of Singaporean Children Aged 6-12 Years.

Pattern analysis of children's diet may provide insights into chronic disease risk in adolescence and adulthood. This study aimed to assess dietary patterns of young Singaporean children using cluster analysis. An existing dataset included 15,820 items consumed by 561 participants (aged 6-12 years) over 2 days of dietary recall. Thirty-seven food groups were defined and expressed as a percentage contribution of total energy. Dietary patterns were identified using k-means cluster analysis. Three clusters were identified, "Western", "Convenience" and "Local/hawker", none of which were defined by more prudent dietary choices. The "Convenience" cluster group had the lowest total energy intake (mean 85.8 ± SD 25.3% of Average Requirement for Energy) compared to the other groups (95.4 ± 25.9% for "Western" and 93.4 ± 25.3% for "Local/hawker", p < 0.001) but also had the lowest calcium intake (66.3 ± 34.7% of Recommended Dietary Allowance), similar to intake in the "Local/hawker" group (69.5 ± 38.9%) but less than the "Western" group (82.8 ± 36.1%, p < 0.001). These findings highlight the need for longitudinal analysis of dietary habit in younger Singaporeans in order to better define public health messaging targeted at reducing risk of major noncommunicable disease.