Iizuka Katsumi, Yanagi Kotone, Deguchi Kanako, Ushiroda Chihiro, Yamamoto-Wada Risako, Ishihara Takuma, Naruse Hiroyuki
Department of Clinical Nutrition, Fujita Health University, Toyoake 470-1192, Japan.
Food and Nutrition Service Department, Fujita Health University Hospital, Toyoake 470-1192, Japan.
Nutrients. 2025 Jul 2;17(13):2205. doi: 10.3390/nu17132205.
: Dietary patterns vary with age and sex. The aim of this study was to clarify the differences in dietary patterns among young and middle-aged Japanese individuals by age group and sex via statistical methods such as alpha diversity and beta diversity analyses. : Using data from a dietary survey of 10 food items during health checkups of 2743 Fujita Health University employees, we examined the effects of age and sex on alpha diversity (Shannon index) and beta diversity (nonmetric multidimensional scaling (NMDS) and RDA). Unlike principal component analysis which assumes linear relationships, redundancy analysis (RDA) incorporates explanatory variables to directly assess how external factors shape multivariate patterns. : The Shannon index increased with age and was greater in males across age groups. Type III ANOVA revealed significant main effects of age ( < 0.001) and sex ( < 0.001), and the effect of the interaction between age and sex approached significance ( = 0.08). Visualization of the NMDS data revealed that women aged 20-29 years and women aged 30 years and older and men aged 20-39 years and men aged 50-59 years have different dietary patterns. The RDA model accounted for 2.01% of the variance (adjusted R = 1.94%), with age and sex contributing 56.7% and 43.3%, respectively. RDA1 and RDA2 were correlated with age (r = 0.26, -0.14) and sex (r = 0.15, 0.21). The RDA1 values increased with age and were greater in females, whereas the RDA2 values decreased with age and were greater in females. RDA1 (1.41% of the total variance in food group intake, 70.1% of the constrained variance) was positively associated with fruits, milk, and seaweed and negatively associated with meat and eggs. In RDA2 (0.60% of total variance, 29.9% contribution), fruits, potatoes, and vegetables had positive effects, whereas fish had negative effects. : Dietary patterns vary by age and sex, with meat, fish, eggs, and fruit as key determinants. Nutritional guidance must account for variations in dietary patterns influenced by age and sex.
饮食模式因年龄和性别而异。本研究的目的是通过α多样性和β多样性分析等统计方法，阐明日本中青年个体在年龄组和性别方面的饮食模式差异。
利用藤田保健大学2743名员工健康检查期间对10种食物的饮食调查数据，我们研究了年龄和性别对α多样性（香农指数）和β多样性（非度量多维尺度分析（NMDS）和冗余分析（RDA））的影响。与假设线性关系的主成分分析不同，冗余分析（RDA）纳入解释变量以直接评估外部因素如何塑造多元模式。
香农指数随年龄增长而增加，且在各年龄组中男性的指数更高。III型方差分析显示年龄（<0.001）和性别（<0.001）有显著的主效应，年龄和性别的交互作用效应接近显著水平（=0.08）。NMDS数据的可视化显示，20 - 29岁的女性、30岁及以上的女性以及20 - 39岁的男性和50 - 59岁的男性有不同的饮食模式。RDA模型解释了2.01%的方差（调整后R = 1.94%），年龄和性别分别贡献了56.7%和43.3%。RDA1和RDA2与年龄（r = 0.26， - 0.14）和性别（r = 0.15，0.21）相关。RDA1值随年龄增加，且在女性中更大，而RDA2值随年龄降低，且在女性中更大。RDA1（占食物组摄入量总方差的1.41%，占受限方差的70.1%）与水果、牛奶和海藻呈正相关，与肉类和蛋类呈负相关。在RDA2（占总方差的0.60%，贡献29.9%）中，水果、土豆和蔬菜有正向影响，而鱼类有负向影响。
饮食模式因年龄和性别而异，肉类、鱼类、蛋类和水果是关键决定因素。营养指导必须考虑到受年龄和性别影响的饮食模式差异。
