Masset Gabriel, Scarborough Peter, Rayner Mike, Mishra Gita, Brunner Eric J
Research Department of Epidemiology and Public Health, University College London,London,UK.
British Heart Foundation Health Promotion Research Group, Nuffield Department of Population Health, University of Oxford,Oxford,UK.
Br J Nutr. 2015 Jun 14;113(11):1800-9. doi: 10.1017/S000711451500094X. Epub 2015 Apr 22.
Higher variety of recommended foods, identified arbitrarily based on dietary guidelines, has been associated with better health status. Nutrient profiling is designed to identify objectively, based on nutrient content, healthier foods whose consumption should be encouraged. The objective was to assess the prospective associations between total food variety (food variety score, FVS) and variety from selected recommended and non-recommended foods (RFV and NRFV, respectively) and risk of chronic disease and mortality. In 1991-3, 7251 participants of the Whitehall II study completed a 127-item FFQ. The FVS was defined as the number of foods consumed more than once a week. (N)RFV(Ofcom) and (N)RFV(SAIN,LIM) were similarly derived selecting healthier (or less healthier) foods as defined by the UK Ofcom and French SAIN,LIM nutrient profile models, respectively. Multi-adjusted Cox regressions were fitted with incident CHD, diabetes, CVD, cancer and all-cause mortality (318, 754, 137, 251 and 524 events, respectively – median follow-up time 17 years). RFV and NRFV scores were mutually adjusted. The FVS (fourth v. first quartile) was associated with a 39 and 26% reduction of prospective CHD and all-cause mortality risk, respectively. The RFV(Ofcom) (third v. first quartile) was associated with a 27 and 35% reduction of all-cause mortality and cancer mortality risk, respectively; similar associations were suggested, but not significant for the RFV(SAIN,LIM). No prospective associations were observed with NRFV scores. The results strengthen the rationale to promote total food variety and variety from healthy foods. Nutrient profiling can help in identifying those foods whose consumption should be encouraged.
根据饮食指南任意确定的推荐食物种类越多，与更好的健康状况相关。营养成分分析旨在根据营养成分客观地确定应鼓励食用的更健康的食物。目的是评估食物总种类（食物种类得分，FVS）以及选定的推荐和非推荐食物的种类（分别为RFV和NRFV）与慢性病风险和死亡率之间的前瞻性关联。在1991 - 1993年，怀特霍尔二世研究的7251名参与者完成了一份包含127个条目的食物频率问卷。FVS被定义为每周食用超过一次的食物数量。（N）RFV（英国通信管理局）和（N）RFV（法国国家食品、环境和职业健康安全局、LIM）的计算方式类似，分别根据英国通信管理局和法国国家食品、环境和职业健康安全局、LIM营养成分模型定义的更健康（或不太健康）的食物来得出。对冠心病、糖尿病、心血管疾病、癌症和全因死亡率（分别为318、754、137、251和524例事件，中位随访时间17年）进行多因素调整的Cox回归分析。RFV和NRFV得分相互调整。FVS（第四四分位数与第一四分位数相比）分别与前瞻性冠心病风险降低39%和全因死亡率风险降低26%相关。RFV（英国通信管理局）（第三四分位数与第一四分位数相比）分别与全因死亡率风险降低27%和癌症死亡率风险降低35%相关；对于RFV（法国国家食品、环境和职业健康安全局、LIM）也有类似关联，但不显著。未观察到与NRFV得分的前瞻性关联。这些结果强化了促进食物总种类和健康食物种类的理论依据。营养成分分析有助于确定那些应鼓励食用的食物。
