Dietary patterns of preschool children based on factor analysis combined with cluster
10.3969/j.issn.1006-2483.2023.01.011
- VernacularTitle:基于因子分析结合聚类分析法的学龄前儿童膳食模式研究
- Author:
Jiao TAN
1
,
2
,
3
,
4
;
Lei SHANG
5
,
6
;
Yong-hong MA
1
,
2
,
3
,
4
,
5
,
6
;
Ke MA
1
,
2
,
3
,
4
;
Hai-rui ZHANG
1
,
2
,
3
,
4
;
Yan-cheng FENG
1
,
2
,
3
,
4
Author Information
1. School of Public Health, Xi'
2. an Medical University
3. Research Center for Medical Prevention and Control of Public Safety of Shaanxi Province , Xi'
4. an , Shaanxi 710021, China
5. School of Public Health , Air Force Medical University , Xi'
6. an , Shaanxi 710038 , China
- Publication Type:Journal Article
- Keywords:
Factor analysis combined with cluster method;
Preschool children;
Dietary pattern
- From:
Journal of Public Health and Preventive Medicine
2023;34(1):49-53
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the dietary intake of preschool children in Northwest China, and provide scientific basis for studying the dietary patterns and characteristics of preschool children and formulating targeted dietary interventions. Methods Using the self-designed “Semi-quantitative Food Frequency Questionnaire for Preschool Children in Northwest China“, a convenient sampling method was used to investigate the dietary intake of children aged 3 to 7 years in Northwest China. The factor analysis combined with the cluster method was used to extract the dietary pattern. Results Through factor analysis of the average daily food intake of preschool children, the results show that the KMO test value was 0.82, Bartlett’s test value was 4 528.97, and the associated probability was <0.001, so factor analysis can be performed. In order to obtain more typical factor components so that the results were easier to explain, under the guidance of nutrition experts, the first 4 common factors were finally retained for analysis, and the cumulative variance contribution rate was 62.17%. On this basis, the number of clusters was 4, and the K-means cluster analysis method was used to cluster the factor scores of various foods for preschool children. According to the proportions of various foods and the characteristics of the foods, The dietary patterns of preschool children can be divided into staple food-based dietary patterns, high-protein dietary patterns, healthy dietary patterns, and high-sugar dietary patterns. Conclusion Using factor analysis method, the scores of each food factor of preschool children were continuous variables, and the results were highly repeatable, and subsequent analysis can be carried out. The factor analysis combined with cluster analysis method extracting the dietary pattern of preschool children that had certain degree of science. According to the characteristics of the four dietary patterns extracted in this study, children's dietary interventions can be targeted to promote children's physical and mental health.
