These measures have been validated for two countries (US and Brazil) against an index designed to reflect WHO healthy diet recommendations (2020) along with two additional recommendations from IARC (2018) and constructed using diet recall data (Herforth et al. 2020). Validation for a further eight countries is in the process of publication (Kennedy et al. 2022). The authors state that these metrics, combined with the MDD-W, can be used to assess current performance and track progress towards healthy diets. The only published study found to date that links these measures with outcomes is an observational study in China that assessed the association of the GDR scores with overweight and obesity in children 7-18 years of age, finding a positive association between the NCD-Risk score and obesity as well as a negative association between the overall GDR score and obesity (Wang et al. 2022).

The **Global Diet Quality Score (GDQS)** is a food-based metric composed of 25 food groups (16 healthy, 7 unhealthy and 2 unhealthy when consumed in excessive amounts) that are important contributors to nutrient intake and/or NCD risk (Bromage et al. 2021). It uses self-reported consumption based on a semiquantitative 24-hour recall. It is currently one of the only diet quality metrics that has been validated against both nutrient adequacy and diet-related NCD risk. A recent study found that the GDQS was better than other metrics (e.g. MDD- W and AHEI, the Alternative Healthy Eating Index from 2010) at predicting changes in weight and waist circumference among women in Mexico (Angulo et al. 2021). Another study for China found that the GDQS was inversely associated with metabolic syndrome and nutrient inadequacy or both (He et al. 2021). The use of the two submetrics allows one to distinguish between diets which are nutrient inadequate due to insufficiency in the diet, and diets which are nutrient-inadequate due to unhealthy food choices. However, this metric has not yet been widely integrated in national surveys and data availability for LMIC are very limited.

There are also two diet quality metrics derived from modeling approaches. The **Global Dietary Database** has sought to consolidate existing quantitative data and produce modeled estimates of individual food and nutrient intake for 188 countries (Miller et al. 2021). These estimates have been used to describe dietary quality at country, regional and global levels using various metrics (Miller et al. 2022) and quantify disease burdens attributable to diet, such as for type 2 diabetes (O’Hearn et al. 2023).

The **Global Burden of Disease Project** uses a set of **15 dietary risk factors** : diets low in: fiber; fruits; legumes; nuts and seeds; polyunsaturated fatty acids (PUFAs); seafood omega-3 fatty acids; vegetables and whole grains; milk; calcium; and diets high in: processed meat; red meat; sodium; sugar-sweetened beverages; and trans fatty acids; these include most of the recommendations from WHO with some additional ones for cancer from IARC (GBD 2017 Diet Collaborators, 2019). They develop Global Burden of Disease estimates of the contribution of dietary risks to the burden of NCDs in adults over the age of 25 across 195 countries, along with their associated impact on mortality and DALYs.

One critique of these modeled estimates points to the fact that evidence on dietary intake from representative populations in LMIC is currently inadequate to produce robust and reliable estimates of intake across countries (Beal et al. 2021). The relevance and face validity of modeled data for country-level work are also often questioned by national stakeholders. Another concern is that GBD 2017 Diet Collaborators’ (2019) estimates of adverse effects of dietary factors (11m deaths annually) far exceed the estimates from other studies cited above of adverse effects of overweight and obesity (4m globally). Some dietary risks affect health directly without necessarily being mediated by obesity, for example consumption of processed meats increases risk for colon cancer. There is also likely an indeterminate amount of double counting in the mortality estimates, given the “adding up” methodology employed (i.e., single dietary components are considered as independent and correlated structure or substitution effects not adequately considered). Diets do not tend to be randomly deficient in protective factors, or randomly contain single dietary risk factors. Rather, many households which have insufficient purchasing power are unable to consume several 7