工具性喂养对9~12岁儿童挑食行为的影响：来自静息态功能磁共振的证据

doi:10.3724/SP.J.1041.2024.00731

摘要/Abstract

摘要：

采用静息态磁共振数据结合机器学习方法在87名9~12岁儿童中探究挑食行为的神经关联, 并检验其在工具性喂养和挑食行为之间的中介作用。结果发现儿童挑食行为与右侧尾状核的局部一致性正相关。功能连接结果表明儿童挑食行为与右侧尾状核−左侧壳核功能连接正相关。预测分析结果显示上述神经发现能够较好的预测儿童挑食行为, 验证了神经结果的稳定性。这表明涉及感觉信息编码和奖赏加工的尾状核和壳核可能在儿童挑食行为的个体差异中起着关键作用。中介模型进一步显示, 工具性喂养能够通过右侧尾状核−左侧壳核功能连接负向影响儿童挑食行为。研究提供了儿童挑食行为稳健的神经基础证据, 并且为从父母喂养方式入手干预改善儿童不良的挑食行为提供理论参考。

关键词: 挑食行为, 工具性喂养, 儿童, 静息态磁共振

Abstract:

Picky eating is a common dietary issue among children characterized by lack of variety of foods consumed due to rejection of familiar (or unfamiliar) foods. The influencing factor model of picky eating behavior in children indicates that environmental and cognitive factors are key elements influencing this. Studies have found that instrumental feeding exacerbates picky eating behavior in children. However, due to the relatively young age of children in previous studies, research on the relationship between instrumental feeding and picky eating behaviors in school-aged children is insufficient. Furthermore, the brain plays a central role in guiding eating behavior; however, to date, limited neuroscientific research on the neural basis of picky eating behaviors in school-aged children exists. This study aimed to utilize resting-state functional magnetic resonance imaging (rs-fMRI) data combined with a machine learning method to explore the neural basis of picky eating behaviors in children. Additionally, it attempted to show the neural mechanisms through which instrumental feeding influences picky eating behavior.

A total of 139 children were recruited for this study. Instrumental feeding and picky eating behaviors were assessed through parent-reported measurements and rs-fMRI was conducted. A total of 87 children were included in the formal analyses as those who did not participate in the two behavioral measurements and with unqualified rs-fMRI scans were excluded. This study utilized regional homogeneity and functional connectivity to evaluate the resting-state neural substrates of picky eating behaviors. Subsequently, a machine learning method is employed to validate the stability of our results. Additionally, a mediation model was constructed to investigate the mediating role of resting-state neural substrates in the relationship between instrumental feeding and picky eating behavior.

Results showed that picky eating behavior was positively correlated with regional homogeneity in the right caudate. Functional connectivity results showed that picky eating behavior was positively correlated with functional connectivity between the right caudate and left putamen. A prediction analysis based on a cross-validation machine learning method indicated a significant correlation between picky eating behavior scores predicted by the aforementioned neural substrates (i.e., regional homogeneity in the right caudate and functional connectivity between the right caudate and left putamen) and the actual observed picky eating behavior scores. The mediation model further suggested that functional connectivity between the right caudate and left putamen could mediate the relationship between instrumental feeding and picky eating behavior. Specifically, instrumental feeding might negatively influence the functional connectivity between the right caudate and left putamen, and further reduce picky eating behavior.

By combining resting-state regional homogeneity and functional connectivity analyses, this study detected altered functional brain activity related to picky eating behaviors in children aged 9 to 12. Specifically, hyperactive neural interactions within the brain areas involved in sensory sensitivity and reward processing may explain the manifestation of picky eating behavior in children. Additionally, instrumental feeding negatively influences picky eating behavior through brain activity in regions involved in sensory sensitivity and reward processing. This study provides new insights into the resting-state neural substrates of children's picky eating behavior, extends the influencing factor model of children's picky eating behavior, and provides theoretical support for interventions to improve poor picky eating behavior in children through parental feeding practices.

Key words: picky eating behavior, instrumental feeding, children, resting-state fMRI

中图分类号:

B845

崔一岑, 张易晓, 陈曦梅, 肖明岳, 刘永, 宋诗情, 高笑, 郭成, 陈红. (2024). 工具性喂养对9~12岁儿童挑食行为的影响：来自静息态功能磁共振的证据. 心理学报, 56(6), 731-744.

CUI Yicen, ZHANG Yixiao, CHEN Ximei, XIAO Mingyue, LIU Yong, SONG Shiqing, GAO Xiao, GUO Cheng, CHEN Hong. (2024). The impact of instrumental feeding on picky eating behavior in children aged 9 to 12: Evidence from resting-state fMRI. Acta Psychologica Sinica, 56(6), 731-744.

图/表 5

表1 所有变量的描述性统计和相关结果(N = 87)

变量	平均值	标准差	范围	1	2	3	4
1 年龄	10.07	0.96	9~12	-
2 BMI	18.61	3.57	12.76~29.81	0.24^*	-
3 头动	0.18	0.13	0.05~0.59	−0.25^*	−0.08	-
4 挑食行为	16.10	4.28	6~28	0.05	−0.01	0.18	-
5 工具性喂养	6.47	1.76	2~10	−0.19	−0.16	−0.04	−0.26^*

图1 与儿童挑食行为相关的显著脑区: (a)儿童挑食行为与右侧尾状核的局部一致性正相关。颜色条表示t值。(b)儿童挑食行为与右侧尾状核处局部一致性相关的散点图。

表2 儿童挑食行为与全脑ReHo值和功能连接的相关分析结果表

脑区	峰值点坐标			体素量	t值
脑区	X Y Z			体素量	t值
与ReHo相关的脑区
右侧尾状核	18	21	0	139	0.54
与功能连接相关的脑区（以右侧尾状核为种子点）
左侧壳核	−21	15	12	214	0.57

图2 与挑食行为相关的功能连接: (a)儿童挑食行为与右侧尾状核−左侧壳核功能连接显著相关。L = 左侧; R = 右侧。(b)儿童挑食行为与右侧尾状核−左侧壳核功能连接相关的散点图。

图3 工具性喂养影响儿童挑食行为的中介模型注：RSFC: 静息态功能连接; *p < 0.05, **p < 0.01, ***p < 0.001

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