Centre for Community Child Health, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria, Australia.
J Epidemiol Community Health. 2017 Dec;71(12):1152-1160. doi: 10.1136/jech-2017-209641. Epub 2017 Oct 9.
Social patterning of dietary-related diseases may partly be explained by population disparities in children's diets. This study aimed to determine which early life socioeconomic factors best predict dietary trajectories across childhood.
For waves 2-6 of the Baby (B) Cohort (ages 2-3 to 10-11 years) and waves 1-6 of the Kindergarten (K) Cohort (ages 4-5 to 14-15 years) of the Longitudinal Study of Australian Children, we constructed trajectories of dietary scores and of empirically derived dietary patterns. Dietary scores, based on the Australian Dietary Guidelines, summed children's consumption frequencies of seven groups of foods or drinks over the last 24 hours. Dietary patterns at each wave were derived using factor analyses of 12-16 food or drink items. Using multinomial logistic regression analyses, we examined associations of baseline single (parental education, remoteness area, parental employment, income, food security and home ownership) and composite (socioeconomic position and neighbourhood disadvantage) factors with adherence to dietary trajectories.
All dietary trajectory outcomes across both cohorts showed profound gradients by composite socioeconomic position but not by neighbourhood disadvantage. For example, odds for children in the lowest relative to highest socioeconomic position quintile being in the 'never healthy' relative to the 'always healthy' score trajectory were OR=16.40, 95% CI 9.40 to 28.61 (B Cohort). Among the single variables, only parental education consistently predicted dietary trajectories.
Child dietary trajectories vary profoundly by family socioeconomic position. If causal, reducing dietary inequities may require researching underlying pathways, tackling socioeconomic inequities and targeting health promoting interventions to less educated families.
饮食相关疾病的社会模式可能部分可以通过儿童饮食方面的人口差异来解释。本研究旨在确定哪些早期社会经济因素最能预测整个儿童期的饮食轨迹。
本研究使用澳大利亚儿童纵向研究的婴儿（B）队列（2-3 岁至 10-11 岁）的第 2-6 波和幼儿园（K）队列（4-5 岁至 14-15 岁）的第 1-6 波的数据，构建了饮食评分和经验衍生的饮食模式轨迹。饮食评分基于澳大利亚饮食指南，汇总了儿童在过去 24 小时内七种食物或饮料的消费频率。在每个波次，通过对 12-16 种食物或饮料项目进行因子分析得出饮食模式。使用多项逻辑回归分析，我们检验了基线单一（父母教育程度、偏远地区、父母就业状况、收入、食品安全和住房所有权）和综合（社会经济地位和社区不利条件）因素与饮食轨迹的关系。
在两个队列的所有饮食轨迹结果中，综合社会经济地位都显示出明显的梯度，但社区不利条件则没有。例如，在 B 队列中，处于最低社会经济地位五分位数的儿童与处于“始终健康”评分轨迹的儿童相比，处于“从不健康”评分轨迹的可能性为 OR=16.40，95%CI 为 9.40 至 28.61。在单一变量中，只有父母教育程度始终可以预测饮食轨迹。
儿童饮食轨迹差异明显取决于家庭社会经济地位。如果存在因果关系，减少饮食不平等可能需要研究潜在途径，解决社会经济不平等问题，并针对教育程度较低的家庭开展促进健康的干预措施。
