Brandt Eric J, Leung Cindy W, Chang Tammy, Ayanian John Z, Banerjee Mousumi, Kirch Matthias, Mozaffarian Dariush, Nallamothu Brahmajee K
Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States; Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
J Nutr. 2025 Aug;155(8):2685-2699. doi: 10.1016/j.tjnut.2025.06.002. Epub 2025 Jun 9.
Naturally occurring dietary patterns are not well described among individuals with cardiovascular disease (CVD) or cardiometabolic risk factors (i.e., diabetes, hypertension, obesity, and dyslipidemia), particularly considering socioeconomic vulnerability.
We investigated major dietary patterns in the United States and their distribution by prevalent CVD, cardiometabolic risk factors, and socioeconomic vulnerability.
This cross-sectional study analyzed data from 32,498 noninstitutionalized adults who participated in the National Health and Nutrition Examination Survey (2009-2020). We used principal component analysis to identify dietary patterns. Using multiple linear regression, we tested the association of prevalent CVD, cardiometabolic risk factors, and socioeconomic vulnerability [number of social risk factors and Supplemental Nutrition Assistance Program (SNAP) participation status] with each pattern.
Four dietary patterns were identified: processed/animal foods (high-refined grains, added sugars, meats, and dairy), prudent (high vegetables, nuts/seeds, oils, seafood, and poultry), legume, and fruit/whole grain/dairy, which together explained 29.2% of the dietary variance. After adjustment for age, gender, race and ethnicity, cohort year, and total energy intake, the processed/animals foods pattern associated (β-coefficient for difference in principal component score) positively with diabetes [0.08 (0.01, 0.14)], hypertension [0.11 (0.06, 0.16)], obesity [0.15 (0.11, 0.19)], higher social risk score (P-trend < 0.001), income-eligible SNAP nonparticipation [0.16 (0.09, 0.23)], and SNAP participation [0.23 (0.17, 0.29)]. The prudent pattern associated negatively with hypertension [-0.09 (-0.14, -0.04)], obesity [-0.11 (-0.16, -0.06)], higher social risk score (P-trend < 0.001), income-eligible SNAP nonparticipation [-0.14 (-0.21, -0.06)], and SNAP participation [-0.30 (-0.35, -0.24)]. The legume pattern was associated negatively with CVD [-0.09 (-0.15, -0.02)] and obesity [-0.08 (-0.12, -0.04)], and positively with income-eligible SNAP nonparticipation [0.11 (0.04, 0.18)]. The fruit/whole grain/dairy pattern was associated positively with diabetes [0.08 (0.01, 0.15)] and negatively with hypertension [-0.21 (-0.26, -0.15)], obesity [-0.23 (-0.28, -0.18)], higher social risk score (P-trend < 0.001), and SNAP participation [-0.19 (-0.25, -0.12)].
Empirical dietary patterns in the United States vary by CVD, cardiometabolic risk factors, and socioeconomic vulnerability. Initiatives to improve nutrition should consider these naturally occurring dietary patterns and their variation in key subgroups.
在患有心血管疾病（CVD）或存在心血管代谢危险因素（即糖尿病、高血压、肥胖和血脂异常）的个体中，对自然形成的饮食模式描述不足，尤其是考虑到社会经济脆弱性。
我们调查了美国的主要饮食模式及其在普遍存在的心血管疾病、心血管代谢危险因素和社会经济脆弱性方面的分布情况。
这项横断面研究分析了参与美国国家健康与营养检查调查（2009 - 2020年）的32498名非机构化成年人的数据。我们使用主成分分析来确定饮食模式。通过多元线性回归，我们测试了普遍存在的心血管疾病、心血管代谢危险因素和社会经济脆弱性[社会风险因素数量和补充营养援助计划（SNAP）参与状况]与每种模式之间的关联。
确定了四种饮食模式：加工/动物性食物（高精制谷物、添加糖、肉类和乳制品）、谨慎型（高蔬菜、坚果/种子、油类、海鲜和家禽）、豆类以及水果/全谷物/乳制品，这四种模式共同解释了饮食差异的29.2%。在对年龄、性别、种族和族裔、队列年份以及总能量摄入进行调整后，加工/动物性食物模式与糖尿病[0.08（0.01，0.14）]、高血压[0.11（0.06，0.16）]、肥胖[0.15（0.11，0.19）]、较高的社会风险评分（P趋势<0.001）、符合收入条件的SNAP未参与[0.16（0.09，0.23）]以及SNAP参与[0.2（0.17，0.29）]呈正相关。谨慎型模式与高血压[-0.09（-0.14，-0.04）]、肥胖[-0.11（-0.16，-0.0）]、较高的社会风险评分（P趋势<0.001）、符合收入条件的SNAP未参与[-0.14（-0.21，-0.06）]以及SNAP参与[-0.30（-0.35，-0.24）]呈负相关。豆类模式与心血管疾病[-0.09（-0.15，-0.02）]和肥胖[-0.08（-0.12，-0.04）]呈负相关，与符合收入条件的SNAP未参与[0.11（0.04，0.18）]呈正相关。水果/全谷物/乳制品模式与糖尿病[0.08（0.01，0.15）]呈正相关，与高血压[-0.21（-0.26，-0.15）]、肥胖[-0.23（-0.28，-0.18）]、较高的社会风险评分（P趋势<0.001）以及SNAP参与[-0.19（-0.25，-0.12）]呈负相关。
美国的经验性饮食模式因心血管疾病、心血管代谢危险因素和社会经济脆弱性而异。改善营养的举措应考虑这些自然形成的饮食模式及其在关键亚组中的差异。
