Watanabe Daiki, Murakami Haruka, Gando Yuko, Kawakami Ryoko, Tanisawa Kumpei, Ohno Harumi, Konishi Kana, Sasaki Azusa, Morishita Akie, Miyatake Nobuyuki, Miyachi Motohiko
Department of Physical Activity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Shinjuku-ku, Japan.
Institute for Active Health, Kyoto University of Advanced Science, Kameoka, Japan.
Front Nutr. 2022 Feb 8;9:753127. doi: 10.3389/fnut.2022.753127. eCollection 2022.
Many cross-sectional studies have identified modifiable factors such as dietary intake, physique, and physical activity associated with diet quality but were unable to determine how a specific individual's diet quality changes with these factors. These relationships may vary depending on an individual's dietary intake. We aimed to determine the association between temporal changes in diet quality and concurrent changes in dietary intake, body mass index (BMI), and physical activity according to the diet quality trajectory pattern.
This longitudinal prospective study included 697 Japanese adults aged 26-85 years, at baseline, with available data from at least two dietary intake surveys (4,118 measurements). Dietary intake and physical activity were evaluated using validated dietary questionnaires and a triaxial accelerometer. Diet quality was calculated using the Nutrient-Rich Food Index 9.3 (NRF9.3), while physical activity was calculated based on the duration of activity performed at each level of intensity (sedentary, light, moderate, and vigorous). Body mass index was calculated from the measured height and weight. Statistical analyses involved latent class growth models (LCGM) and random-effect panel data analysis.
During a mean follow-up period of 6.8 years, NRF9.3 scores were assessed, on average, 5.4 times in men and 6.1 times in women. Based on the NRF9.3 score, three separate trajectory groups-"low-increasing," "medium-increasing," and "high-stable"-among individuals aged 26-90 years were identified using LCGM. In the multivariate analysis, the NRF9.3 score trajectory was positively associated with intake of energy, protein, dietary fiber, vitamins A and C, magnesium, and food items, such as fruits and vegetables, and was negatively associated with BMI and the intake of added sugar, saturated fats, sodium, and food items, such as meat and sugar and confectioneries, even after adjusting for covariates. These relationships displayed heterogeneity across the identified NRF9.3 score trajectory groups. In the low-increasing group, an inverse relationship was observed between sedentary behavior and NRF9.3 score trajectory.
We identified modifiable factors associated with temporal changes in diet quality across a wide age range; however, these factors may vary according to the diet quality trajectories. Our findings may help develop effective strategies for improving diet quality, according to the trajectory of diet quality.
许多横断面研究已经确定了与饮食质量相关的可改变因素,如饮食摄入、体格和身体活动,但无法确定特定个体的饮食质量如何随这些因素而变化。这些关系可能因个体的饮食摄入而异。我们旨在根据饮食质量轨迹模式,确定饮食质量的时间变化与饮食摄入、体重指数(BMI)和身体活动的同时变化之间的关联。
这项纵向前瞻性研究纳入了697名年龄在26 - 85岁的日本成年人,在基线时至少有两次饮食摄入调查的可用数据(共4118次测量)。使用经过验证的饮食问卷和三轴加速度计评估饮食摄入和身体活动。使用营养丰富食物指数9.3(NRF9.3)计算饮食质量,而身体活动则根据在每个强度水平(久坐、轻度、中度和剧烈)进行的活动持续时间来计算。根据测量的身高和体重计算体重指数。统计分析涉及潜在类别增长模型(LCGM)和随机效应面板数据分析。
在平均6.8年的随访期内,男性平均评估NRF9.3得分5.4次,女性平均评估6.1次。基于NRF9.3得分,使用LCGM在26 - 90岁的个体中确定了三个不同的轨迹组——“低增长”、“中增长”和“高稳定”。在多变量分析中,即使在调整协变量后,NRF9.3得分轨迹与能量、蛋白质、膳食纤维、维生素A和C、镁以及水果和蔬菜等食物的摄入量呈正相关,与BMI以及添加糖、饱和脂肪、钠以及肉类、糖和糖果等食物的摄入量呈负相关。这些关系在确定的NRF9.3得分轨迹组中表现出异质性。在低增长组中,观察到久坐行为与NRF9.3得分轨迹之间呈负相关。
我们确定了在广泛年龄范围内与饮食质量的时间变化相关的可改变因素;然而,这些因素可能因饮食质量轨迹而异。我们的研究结果可能有助于根据饮食质量轨迹制定改善饮食质量的有效策略。