{"title":"健康植物性饮食模式与肥胖测量轨迹和未来代谢性疾病风险之间的关系:一项前瞻性队列研究","authors":"Chenyu Zhao, Tianrun Wang, Yuping Wang, Xiaocan Jia, Zhixing Fan, Chaojun Yang, Jingwen Fan, Nana Wang, Yongli Yang, Xuezhong Shi, Yifan Shan","doi":"10.1002/fsn3.70790","DOIUrl":null,"url":null,"abstract":"<p>The dynamic and heterogeneous process of obesity measurement can be better assessed by change trajectories. Utilizing multiple metrics to assess obesity could provide more comprehensive insights. Currently, the associations of adiposity measures trajectories with metabolic diseases and plant-based dietary patterns remain unclear. Using latent class mixed modeling approach, we identified body mass index (BMI), waist-to-hip ratio (WHR) and fat mass index (FMI) trajectory groups based on measures acquired at four time points. We examined associations between adiposity measures trajectories and plant-based dietary patterns, using logistic regression. Cox proportional hazards regression models were applied to investigate the association between adiposity measures trajectories and metabolic diseases. We identified two latent classes of BMI trajectories: low-smooth and high-growth-decline, two WHR trajectories: low-growth and high-growth, and two FMI trajectories: low-smooth and high-growth-decline. Participants who had a high healthful plant-based diet index had lower odds of being in the high-growth-decline BMI trajectory (OR = 0.491, 95% CI: 0.402, 0.600), the high-growth WHR trajectory (OR = 0.526, 95% CI: 0.438, 0.632) or the high-growth-decline FMI trajectory (OR = 0.533, 95% CI: 0.446, 0.638). We found that participants in the high-growth-decline BMI trajectory (HR = 1.925, 95% CI: 1.542, 2.404), the high-growth WHR trajectory (HR = 1.314, 95% CI: 1.003, 1.722) or the high-growth-decline FMI trajectory (HR = 1.562, 95% CI: 1.236, 1.975) had higher risks. A healthy plant-based dietary pattern assists in maintaining normal body size over time. Concurrently, long-term stabilization of a normal body size may be linked to a reduced risk of metabolic diseases.</p>","PeriodicalId":12418,"journal":{"name":"Food Science & Nutrition","volume":"13 8","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fsn3.70790","citationCount":"0","resultStr":"{\"title\":\"Association Between Healthful Plant-Based Dietary Pattern and Adiposity Measures Trajectories and Future Metabolic Diseases Risk: A Prospective Cohort Study\",\"authors\":\"Chenyu Zhao, Tianrun Wang, Yuping Wang, Xiaocan Jia, Zhixing Fan, Chaojun Yang, Jingwen Fan, Nana Wang, Yongli Yang, Xuezhong Shi, Yifan Shan\",\"doi\":\"10.1002/fsn3.70790\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The dynamic and heterogeneous process of obesity measurement can be better assessed by change trajectories. Utilizing multiple metrics to assess obesity could provide more comprehensive insights. Currently, the associations of adiposity measures trajectories with metabolic diseases and plant-based dietary patterns remain unclear. Using latent class mixed modeling approach, we identified body mass index (BMI), waist-to-hip ratio (WHR) and fat mass index (FMI) trajectory groups based on measures acquired at four time points. We examined associations between adiposity measures trajectories and plant-based dietary patterns, using logistic regression. Cox proportional hazards regression models were applied to investigate the association between adiposity measures trajectories and metabolic diseases. We identified two latent classes of BMI trajectories: low-smooth and high-growth-decline, two WHR trajectories: low-growth and high-growth, and two FMI trajectories: low-smooth and high-growth-decline. Participants who had a high healthful plant-based diet index had lower odds of being in the high-growth-decline BMI trajectory (OR = 0.491, 95% CI: 0.402, 0.600), the high-growth WHR trajectory (OR = 0.526, 95% CI: 0.438, 0.632) or the high-growth-decline FMI trajectory (OR = 0.533, 95% CI: 0.446, 0.638). We found that participants in the high-growth-decline BMI trajectory (HR = 1.925, 95% CI: 1.542, 2.404), the high-growth WHR trajectory (HR = 1.314, 95% CI: 1.003, 1.722) or the high-growth-decline FMI trajectory (HR = 1.562, 95% CI: 1.236, 1.975) had higher risks. A healthy plant-based dietary pattern assists in maintaining normal body size over time. Concurrently, long-term stabilization of a normal body size may be linked to a reduced risk of metabolic diseases.</p>\",\"PeriodicalId\":12418,\"journal\":{\"name\":\"Food Science & Nutrition\",\"volume\":\"13 8\",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fsn3.70790\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Food Science & Nutrition\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/fsn3.70790\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Science & Nutrition","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/fsn3.70790","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Association Between Healthful Plant-Based Dietary Pattern and Adiposity Measures Trajectories and Future Metabolic Diseases Risk: A Prospective Cohort Study
The dynamic and heterogeneous process of obesity measurement can be better assessed by change trajectories. Utilizing multiple metrics to assess obesity could provide more comprehensive insights. Currently, the associations of adiposity measures trajectories with metabolic diseases and plant-based dietary patterns remain unclear. Using latent class mixed modeling approach, we identified body mass index (BMI), waist-to-hip ratio (WHR) and fat mass index (FMI) trajectory groups based on measures acquired at four time points. We examined associations between adiposity measures trajectories and plant-based dietary patterns, using logistic regression. Cox proportional hazards regression models were applied to investigate the association between adiposity measures trajectories and metabolic diseases. We identified two latent classes of BMI trajectories: low-smooth and high-growth-decline, two WHR trajectories: low-growth and high-growth, and two FMI trajectories: low-smooth and high-growth-decline. Participants who had a high healthful plant-based diet index had lower odds of being in the high-growth-decline BMI trajectory (OR = 0.491, 95% CI: 0.402, 0.600), the high-growth WHR trajectory (OR = 0.526, 95% CI: 0.438, 0.632) or the high-growth-decline FMI trajectory (OR = 0.533, 95% CI: 0.446, 0.638). We found that participants in the high-growth-decline BMI trajectory (HR = 1.925, 95% CI: 1.542, 2.404), the high-growth WHR trajectory (HR = 1.314, 95% CI: 1.003, 1.722) or the high-growth-decline FMI trajectory (HR = 1.562, 95% CI: 1.236, 1.975) had higher risks. A healthy plant-based dietary pattern assists in maintaining normal body size over time. Concurrently, long-term stabilization of a normal body size may be linked to a reduced risk of metabolic diseases.
期刊介绍:
Food Science & Nutrition is the peer-reviewed journal for rapid dissemination of research in all areas of food science and nutrition. The Journal will consider submissions of quality papers describing the results of fundamental and applied research related to all aspects of human food and nutrition, as well as interdisciplinary research that spans these two fields.