In the current context of unsustainable food systems, we aimed to develop and validate an index, the sustainable diet index (SDI), assessing the sustainability of dietary patterns, including multidimensional individual indicators of sustainability. Based on the FAO’s definition of sustainable diets, the SDI includes seven indicators categorised into four standardised sub-indexes, respectively, environmental, nutritional, economic and sociocultural. The index (range: 4–20) was obtained by summing the sub-indexes. We computed the SDI for 29 388 participants in the NutriNet-Santé cohort study, estimated its validity and identified potential socio-demographic or lifestyle differences across the SDI quintile. In our sample, the SDI (mean=12·10/20; 95 % CI 12·07, 12·13) was highly correlated to all the sub-indexes that exerted substantial influence on the participants’ ranking. The environmental and economical sub-indexes were the most and less correlated with the SDI (Pearson R2 0·66 and 0·52, respectively). Dietary patterns of participants with a high SDI (considered as more sustainable) were concordant with the already published sustainable diets. Participants with high SDI scores were more often women (24 %), post-secondary graduates (22 %) and vegetarians or vegans (7 %), without obesity (16 %). Finally, the SDI could be a useful tool to easily assess the sustainability-related changes in dietary patterns, estimate the association with long-term health outcomes and help guide future public health policies.

Health is a multidimensional and continual concept. Traditional latent analytic approaches have inherent deficits in capturing the complex nature of the concept; however, the Grade of Membership (GoM) model is well suited for this problem. We applied the GoM method to a set of 31 indicators to construct ideal profiles of health status based on physical, mental and social support items among 848 adult twins from Qingdao, China. Four profiles were identified: healthy individuals (pure type I), individuals with personality disorders (pure type II), individuals with mental impairments (pure type III) and individuals with physical impairments (pure type IV). The most frequently occurring combination in this population was profiles I, II, IV (14.74%), followed by profiles I, II, III, IV (13.44%), and then type I (11.08%). Only 13.56% of subjects fell completely into one single pure type, most individuals exhibited some of the characteristics of two or more pure types. Our results indicated that, compared to conventional statistical methods, the GoM model was more suited to capture the complex concept of health, reflecting its multidimensionality and continuity, while also exhibiting preferable reliability. This study also made an important contribution to research on GoM application in non-independent samples.