for which overweight/obesity is a major risk factor. These costs include treatment costs, disability-adjusted life-year (DALY) losses, and productivity losses. Table 4 summarizes the major costs included in previous studies, with brief descriptions of how they are calculated. It is proposed to use similar standard methods in the methodology proposed in the next section.

# 5. A Proposed Methodology for Estimating Economic Costs of Unhealthy Diets at the Country Level

Malnutrition in all its forms (as measured by undernutrition/overweight/obesity) is not synonymous with unhealthy diets. There are individuals who have impaired growth despite nutrient-adequate diets because of other factors. Infection (itself related to vaccine status and the water and sanitation environment) is a key factor (Figure 2). Similarly, there are individuals who are overweight/obese despite their diet because of other factors, such as exposure to an obesogenic environment (Figure 2). Finally, having a healthy weight does not imply having a healthy diet. Individuals may maintain a healthy weight while consuming a diet that is inadequate in micronutrients or not balanced or not moderated. One example of individuals with healthy weight but unhealthy diets is those consuming excess salt which can increase hypertension and risks of cardiovascular disease.

Hence, although it is useful to employ cost methodologies similar to those of existing studies of undernutrition and overweight/obesity, adjustments are required since healthy weight does not imply the diet is healthy, nor is the converse true.

Figure 3 illustrates this. The figure illustrates a hypothetical distribution of nutritional status in the population (in this case the population mean weight is in the healthy range, but that is not necessarily the case). The vertical lines delineate the population fractions who are with underweight, healthy weight, and overweight/obese. The dotted horizontal lines separate those within each nutritional status who have healthy diets and those who do not. We will use these fractions to estimate the associated economic costs, using data on stunting in children under 5 years of age to project productivity costs across the life course, and using data on adults 18 years and over on overweight/obesity since the vast majority of productivity losses are in this age group. Hence while the FOLU (2019) study equates the combined costs of underweight and overweight/obesity on morbidity and mortality to human costs of the food system, Figure 3 shows that the situation is more complex. However, estimating the relative proportions of those with undernutrition, of healthy weight and overweight/obese with healthy diets, is not trivial.

We propose the following methods. To distinguish the share of child undernutrition associated with inadequate dietary intake and that associated with other factors such as infection, we will use the Lives Saved Tool (LiST: <u>https://www.livessavedtool.org). We can then attribute this cost share (projecting</u> forward to lifetime productivity losses) to estimate the proportion of the costs of child undernutrition attributable to unhealthy diets.

NCD costs (both treatment costs and DALY/productivity costs) among the adult population (18 years and older) are the major cost associated with unhealthy diets for those who are healthy weight and those who are overweight/obese. To estimate the proportion of NCD costs attributable to unhealthy diets we propose to use the following two equations:

- (1) O&O = f(food choice, other)

- (2) NCD risk = g(O&O, food choice, other)

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