인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
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논문 기본 정보
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초록·키워드
Picky eating in early childhood is associated with repeated low intake of particular food groups, and childcare meal services provide regular opportunities for children to encounter diverse foods. Previous studies, however, have relied largely on questionnaires and single-time-point measures, limiting the objective assessment of how much children actually consume and how intake changes over time. This study aimed to examine changes in meal intake rates and picky-eating-like record rates among preschool children using AI food-scanner data collected during routine childcare meal services. We retrospectively analyzed 136,517 food records from 170 preschool children in 12 childcare centers in Changwon, Korea, comparing an introduction period (0–60 days) with a follow-up period (300–360 days) over approximately 12 months. A picky-eating-like record was defined as a food record with an intake rate below 10%, representing an operational rather than a clinical indicator. The overall intake rate increased from 63.9% to 68.5% (Wilcoxon p =.002, dz=0.31), and the overall picky-eating-like record rate decreased from 22.9% to 19.2% (p <.001, dz=−0.32); both changes were more evident among children with low or medium baseline intake. By food group, the record rate decreased for vegetables, legumes, meat, and grains, but not for fish. Generalized estimating equations showed decreasing odds of a picky-eating-like record per relative month (adjusted odds ratio 0.970, 95% CI 0.957–0.984). As this was a single-group observational analysis without a control group, causal effects cannot be inferred, and the stronger changes among children with low or medium baseline intake should be interpreted with the possibility of regression to the mean in mind. These findings suggest that AI food-scanner data can support objective, food-group-specific monitoring of intake in childcare settings and may help identify children with repeatedly low intake of specific food groups.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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