Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle Upon Tyne, UK.
BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.
Eur J Clin Nutr. 2018 Feb;72(2):207-219. doi: 10.1038/s41430-017-0004-y. Epub 2017 Dec 15.
BACKGROUND/OBJECTIVES: To identify predictors of obesity in adults and investigate to what extent these predictors are independent of other major confounding factors.
SUBJECTS/METHODS: Data collected at baseline from 1441 participants from the Food4Me study conducted in seven European countries were included in this study. A food frequency questionnaire was used to measure dietary intake. Accelerometers were used to assess physical activity levels (PA), whereas participants self-reported their body weight, height and waist circumference via the internet.
The main factors associated (p < 0.05) with higher BMI per 1-SD increase in the exposure were age (β:1.11 kg/m), intakes of processed meat (β:1.04 kg/m), red meat (β:1.02 kg/m), saturated fat (β:0.84 kg/m), monounsaturated fat (β:0.80 kg/m), protein (β:0.74 kg/m), total energy intake (β:0.50 kg/m), olive oil (β:0.36 kg/m), sugar sweetened carbonated drinks (β:0.33 kg/m) and sedentary time (β:0.73 kg/m). In contrast, the main factors associated with lower BMI per 1-SD increase in the exposure were PA (β:-1.36 kg/m), intakes of wholegrains (β:-1.05 kg/m), fibre (β:-1.02 kg/m), fruits and vegetables (β:-0.52 kg/m), nuts (β:-0.52 kg/m), polyunsaturated fat (β:-0.50 kg/m), Healthy Eating Index (β:-0.42 kg/m), Mediterranean diet score (β:-0.40 kg/m), oily fish (β:-0.31 kg/m), dairy (β:-0.31 kg/m) and fruit juice (β:-0.25 kg/m).
These findings are important for public health and suggest that promotion of increased PA, reducing sedentary behaviours and improving the overall quality of dietary patterns are important strategies for addressing the existing obesity epidemic and associated disease burden.
背景/目的:确定成年人肥胖的预测因素,并研究这些预测因素在多大程度上独立于其他主要混杂因素。
对象/方法:本研究纳入了在欧洲七个国家开展的 Food4Me 研究中基线时的 1441 名参与者的数据。使用食物频率问卷来测量膳食摄入量。使用加速度计来评估体力活动水平(PA),而参与者通过互联网自行报告体重、身高和腰围。
与暴露因素每增加 1 个标准差相关的主要因素(p<0.05)为年龄(β:1.11kg/m)、加工肉(β:1.04kg/m)、红肉(β:1.02kg/m)、饱和脂肪(β:0.84kg/m)、单不饱和脂肪(β:0.80kg/m)、蛋白质(β:0.74kg/m)、总能量摄入(β:0.50kg/m)、橄榄油(β:0.36kg/m)、含糖碳酸饮料(β:0.33kg/m)和久坐时间(β:0.73kg/m)。相比之下,与暴露因素每增加 1 个标准差相关的主要因素为 PA(β:-1.36kg/m)、全谷物(β:-1.05kg/m)、膳食纤维(β:-1.02kg/m)、水果和蔬菜(β:-0.52kg/m)、坚果(β:-0.52kg/m)、多不饱和脂肪(β:-0.50kg/m)、健康饮食指数(β:-0.42kg/m)、地中海饮食评分(β:-0.40kg/m)、油性鱼(β:-0.31kg/m)、乳制品(β:-0.31kg/m)和果汁(β:-0.25kg/m)。
这些发现对公共健康很重要,表明促进增加 PA、减少久坐行为和改善整体饮食模式质量是应对现有肥胖流行和相关疾病负担的重要策略。