acceptable level of dietary adequacy for 11 micronutrients (Martin-Prevel et al. 2017). Diet diversity data have been collected for a sufficient number of years and countries such that there is a body of research linking these measures with nutritional status.

Research suggests that **MDD for young children (6-23 months)** is associated with micronutrient adequacy (Molani-Gol et al. 2023), improved linear growth in some contexts (Gassara and Chen 2021), and lower risk of anemia (Donkor et al. 2021; Kathuria et al. 2023; Molla et al. 2020), but there is no strong indication of links with overweight or obesity. Recently, **egg and flesh food consumption** (which is a component of MDD) was included as an indicator of nutrient-sufficient diets among young children 6-23 months (WHO and UNICEF 2021) and data are widely available for LMICs (UNICEF 2022). Observational studies suggest a strong association for consumption of animal-source foods (ASF) with improved linear growth (Headey, Hirvonen and Hoddinott 2018; Krasevec et al. 2017; Zaharia et al. 2021), while systematic reviews of controlled trials found mixed results (Eaton et al. 2019; Shapiro et al. 2019).

Data collection began more recently for **MDD for non-pregnant women of reproductive age (15-49 years).** MDD-W is now being collected through large-scale DHS surveys in at least 24 countries (although, at the time of writing, results were available for only a limited number) as well as through Gallup World Poll surveys using telephone-based interviews (2021-2022 results available for women 15-49 years for 55 countries plus Palestine). As for children, MDD-W has a strong correlation with nutrient adequacy of diets (Martin-Prevel et al. 2017) but dietary diversity (i.e., not focusing on MDD-W only) has not shown consistent relationship with overweight or obesity and NCDs (Salehi-Abargouei et al. 2016; Vadiveloo, Dixon and Parekh 2013, Verger et al. 2021).

To assess whether a diet is **healthy,** quantitative dietary intake data are viewed as the reference, using detailed data on foods consumed. However, there is only very limited availability of validated metrics based on quantitative data that are well-suited for monitoring healthy diets in LMICs (Miller Micha and Mozaffarian 2020; WHO and UNICEF 2021). When quantitative dietary survey data are not available, the most common alternative approach in LMIC is to assess consumption of specific food groups (both protective and risk-inducing) across the previous day (or other such time interval). These data have only been collected relatively recently, and various alternative metrics have been suggested, such that the methodology for assessing these variables and their link with health and nutritional outcomes is still evolving. Another alternative method of data collection is to use food frequency questionnaires: these have the disadvantages that they are not quantitative and individuals may not recall as accurately over a longer period, but the advantage that better reflect the long-run intake of an individual. What is or is not healthy is frequently defined relative to WHO recommendations for a healthy diet for individuals 15-65 (WHO 2019, reproduced for convenience in Appendix Table 6).

Various metrics have been developed and used to assess whether diets of **adults aged 15 years and older, both men and women** are healthy, a literature which is evolving. Metrics have been developed to assess consumption of specific food groups associated with increased risk of negative nutrition/health outcomes (e.g. ultra-processed foods, sugar-sweetened beverages), as well as combinations of food groups that are recommended either for increased or limited consumption. The strengths and limitations of these indicators for this work are summarized in Table 3.

The Global Diet Quality Project provides new nationally representative data on prevalence of consumption of food groups for 37 LMIC (and up to 54 countries by 2023) (Global Diet Quality Project, 2022), using self-reported consumption of foods from different groups based on non-quantitative 24-hour recalls (Herforth et al. 2020). These data can be used to construct several metrics at the population level. The **Global Dietary Recommendations (GDR) Score** has two components, NCD-Protect and NCD-Risk.

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