direct medical costs. Bardach and colleagues (2023) produced similar estimates for children, adolescents and adults in Argentina alone.

Walters and colleagues (2019) estimated the global human and economic costs of not breastfeeding according to recommendations, including 974,956 cases of childhood obesity each year, 595,379 childhood deaths per year (659 months) from diarrhea and pneumonia, and 98,243 women’s deaths from cancer (breast and ovarian) and T2DM. The total annual global losses associated with inadequate breastfeeding are estimated to be between US$257 billion and US$341 billion (0.37%-0.70% of global gross national income), including US$1.1 billion in health care costs, US$53.7 billion in economic losses due to premature mortality, and US$285.4 billion in cognitive losses.

# Search 2: Evidence on the link between diet quality and health/nutrition outcomes **Search results and characteristics of selected studies**

The study selection process for the second literature search objective is shown in **Figure 3** . The total number of records screened, after removing duplicates was 2,335 and 222 full texts were screened. We identified a total of 82 systematic reviews with meta-analyses (SRM) that included data from LMICs and estimated the burden of nutrition and/or health outcomes associated with specific dietary risk factors. The following sections provide an overview of the evidence available for the diet’s contribution to nutrition and health outcomes, organized by life-stage group.

## Pregnant and lactating women

A total of 19 SRM articles were found that included women of reproductive age in LMICs and assessed the association of diet with maternal and/or neonatal nutrition and health outcomes. **See Table 4.**

### **Maternal nutrition outcomes**

Five (5) SRM assessed risk factors for maternal nutrition outcomes, including anemia (Seid et al. 2023; Geta, Gebremedhin, and Omigbodun 2022; J. Zhang et al. 2022), thinness (Getaneh et al. 2021), and zinc deficiency (Berhe, Gebrearegay, and Gebremariam 2019). Four of the five were based either exclusively or dominantly on studies in Ethiopia, with extensive overlap of studies included. All five SRM included dietary diversity as a risk factor and proxy for diet quality during pregnancy. Low diet diversity was associated with higher risk of maternal anemia, with the effect size estimates ranging from 2.15 to 2.61. However, there was heterogeneity in the number of food groups and dietary diversity score (DDS) cutoffs used to define low or inadequate diet diversity across the studies included in the SRM.

Consumption of specific food groups (e.g. meat, dark green leafy vegetables) relevant to anemia as an outcome was assessed in two studies. Risk of anemia was over two times higher among pregnant women eating meat ≤1 time per week (OR 2.02; 95% CI 1.55, 2.50) and those eating vegetables ≤3 times per week (OR 2.97; 95% CI 1.59, 4.34) (J. Zhang et al. 2022). In a review of four studies from Ethiopia, zinc deficiency was also associated with a low intake of ASF (OR 2.57; 95% CI 1.80, 3.66) and low dietary diversity (OR 2.12; 95% CI 1.28, 3.53) (Berhe et al. 2022).

### **Maternal health outcomes**

Twelve (12) SRM summarized the evidence for the contribution of diet during or before pregnancy to maternal health outcomes, including gestational diabetes, hypertension, pre-eclampsia and gestational weight gain. Three of these assessed the association of maternal adherence to a ‘healthy’ or ‘unhealthy’ dietary pattern (Abdollahi et al. 2021; Chia et al. 2019; Kibret et al. 2019; Haghighatdoost et al. 2023; X. Gao et al. 2023; Hassani Zadeh, Boffetta, and Hosseinzadeh 2020) with various maternal health outcomes during pregnancy. Paula et al. (2022) estimated the risks during pregnancy of UPF-rich diet consumption.

**_Gestational diabetes mellitus (GDM)_** – A total of 25 effect estimates for GDM were recorded. Dietary risk factors for GDM included low diet diversity in two Ethiopian studies (effect size 1.51; 95% CI 1.25, 1.83) (Beyene et al. 2023) and unhealthy food intake, including fried food (Cui et al. 2023), fast food (Cui et al. 2023; Quan et al. 2021), red and processed meat (Cui et al. 2023; Quan et al. 2021), and a diet rich in UPF (Paula et al. 2022). Women

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