College of Health, Massey University, Auckland 0632, New Zealand.
Department of Statistics, University of Auckland, Auckland 1010, New Zealand.
Nutrients. 2020 Nov 8;12(11):3425. doi: 10.3390/nu12113425.
Dietary patterns analyse combinations of foods eaten. This cross-sectional study identified dietary patterns and their nutrients. Associations between dietary patterns and socio-demographic and lifestyle factors were examined in older New Zealand adults. Dietary data (109-item food frequency questionnaire) from the Researching Eating, Activity and Cognitive Health (REACH) study ( = 367, 36% male, mean age = 70 years) were collapsed into 57 food groups. Using principal component analysis, three dietary patterns explained 18% of the variation in diet. Dietary pattern associations with sex, age, employment, living situation, education, deprivation score, physical activity, alcohol, and smoking, along with energy-adjusted nutrient intakes, were investigated using regression analysis. Higher 'Mediterranean' dietary pattern scores were associated with being female, higher physical activity, and higher education ( < 0.001, R = 0.07). Higher 'Western' pattern scores were associated with being male, higher alcohol intake, living with others, and secondary education ( < 0.001, R = 0.16). Higher 'prudent' pattern scores were associated with higher physical activity and lower alcohol intake ( < 0.001, R = 0.15). There were positive associations between beta-carotene equivalents, vitamin E, and folate and 'Mediterranean' dietary pattern scores ( < 0.0001, R ≥ 0.26); energy intake and 'Western' scores ( < 0.0001, R = 0.43); and fibre and carbohydrate and 'prudent' scores ( < 0.0001, R ≥ 0.25). Socio-demographic and lifestyle factors were associated with dietary patterns. Understanding relationships between these characteristics and dietary patterns can assist in health promotion.
饮食模式分析的是所摄入食物的组合。本横断面研究确定了饮食模式及其营养成分。研究在新西兰老年人群中调查了饮食模式与社会人口学和生活方式因素之间的关联。REACH 研究（=367 人，36%为男性，平均年龄为 70 岁）的饮食数据（109 项食物频率问卷）被合并为 57 种食物组。使用主成分分析，三种饮食模式解释了饮食变化的 18%。通过回归分析研究了饮食模式与性别、年龄、就业、居住状况、教育程度、贫困评分、身体活动、酒精和吸烟以及能量调整后的营养素摄入量之间的关联。更高的“地中海”饮食模式评分与女性、更高的身体活动和更高的教育程度相关（<0.001，R=0.07）。更高的“西方”模式评分与男性、更高的酒精摄入量、与他人同住和中等教育程度相关（<0.001，R=0.16）。更高的“谨慎”模式评分与更高的身体活动和更低的酒精摄入量相关（<0.001，R=0.15）。β-胡萝卜素当量、维生素 E 和叶酸与“地中海”饮食模式评分呈正相关（<0.0001，R≥0.26）；能量摄入与“西方”评分呈正相关（<0.0001，R=0.43）；膳食纤维、碳水化合物和“谨慎”评分呈正相关（<0.0001，R≥0.25）。社会人口学和生活方式因素与饮食模式相关。了解这些特征与饮食模式之间的关系有助于促进健康。
