Ziba Bahar, Hosseini Seyed Ahmad, Cheraghian Bahman, Fathi Mojdeh, Mansoori Anahita
School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Nutrition and Metabolic Diseases Research Center, Clinical Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
BMC Endocr Disord. 2025 Apr 11;25(1):97. doi: 10.1186/s12902-024-01825-9.
Obesity is a multi-factorial metabolic disorder, the development and progression caused by genetic, physiological, metabolic, socio-economic, and lifestyle factors (especially physical activity and diet). Therefore, considering the high prevalence of obesity and its complications, and considering that dietary patterns are different in different populations and geographical locations, the present study aims to identify and investigate the relationship between dietary patterns and obesity diseases in the adult population of the Hovizeh city.
5821 participants (2076 obese group and 3745 not obese group) from Hoveyzeh cohort study for this case-control study were chosen. Data related to dietary, demographic, anthropometric, and physical activity information were obtained through a questionnaire. Dietary patterns were identified using factor analysis. The logistic regression method with adjustment for demographic factors, energy intake, physical activity, and blood pressure and diabetic medication was used to determine the relationship between significant food patterns and obesity.
In this study, four major food patterns were identified: 1) Healthy dietary pattern characterized by a high intake of vegetables and high-protein foods,2) Traditional Defined by high consumption of green vegetables, onions, garlic, fruits, refined grains, white meat, liquid oils, and tomatoes, 3) Sweets and snacks, 4) Good oils. Although there was a significant association between sweets and snacks pattern and obesity risk in the crude model (P < 0.05), this association was no longer significant after adjusting for confounding factors. Good oils pattern showed a significant relationship with obesity in the crud and first adjusted model (P < 0.05), but this association was also not significant after adjusting for blood pressure and diabetes medication use. None of these dietary patterns were significantly associated with obesity or other anthropometric indicators after full adjustments for confounders.
Identifying dietary patterns that influence obesity within a population helps inform strategies for obesity prevention and management. However, in this study, no significant association was found between the identified dietary patterns and obesity.
Not applicable.
肥胖是一种多因素代谢紊乱疾病，其发生和发展由遗传、生理、代谢、社会经济和生活方式因素（尤其是身体活动和饮食）引起。因此，鉴于肥胖及其并发症的高患病率，以及考虑到不同人群和地理位置的饮食模式存在差异，本研究旨在识别和调查霍维泽市成年人群中饮食模式与肥胖疾病之间的关系。
本病例对照研究选取了来自霍维泽队列研究的5821名参与者（2076名肥胖组和3745名非肥胖组）。通过问卷调查获取与饮食、人口统计学、人体测量学和身体活动信息相关的数据。使用因子分析确定饮食模式。采用逻辑回归方法，并对人口统计学因素、能量摄入、身体活动、血压和糖尿病用药进行调整，以确定重要食物模式与肥胖之间的关系。
在本研究中，确定了四种主要食物模式：1）以高摄入蔬菜和高蛋白食物为特征的健康饮食模式；2）传统模式，其特点是大量食用绿色蔬菜、洋葱、大蒜、水果、精制谷物、白肉、液体油和西红柿；3）甜食和零食模式；4）优质油模式。尽管在未调整模型中甜食和零食模式与肥胖风险之间存在显著关联（P<0.05），但在调整混杂因素后，这种关联不再显著。优质油模式在未调整模型和首次调整模型中与肥胖存在显著关系（P<0.05），但在调整血压和糖尿病用药使用情况后，这种关联也不显著。在对混杂因素进行全面调整后，这些饮食模式均与肥胖或其他人体测量指标无显著关联。
识别影响人群肥胖的饮食模式有助于为肥胖预防和管理策略提供信息。然而，在本研究中，未发现所确定的饮食模式与肥胖之间存在显著关联。
不适用。
