- Variables are not always available for the same population group, for example the most complete recent data on underweight/overweight (measured using BMI) in adults are for non-pregnant women 20-49, whereas hypertension and diabetes prevalence are available for all adults 18+;

- It is impossible to control for confounding variables;

- There may be differences in reporting methods for the same variables;

- Current prevalence of overweight in adults does not only depend on current diet, but on the diet trajectory over the life course to date;

- Risks of NCD similarly do not only depend on current diet, but on the diet trajectory over the life course to date; and

- Time trends (in per capita calorie supply and overweight/obesity for example) may mean that different age cohorts in the population have different health risks, such that analysis should be undertaken for narrower age cohorts and not for all adults combined.

Hence, the results from cross-country regressions presented here are only exploratory, pending more careful analysis using individual country data. Sample sizes for the regressions are modest (generally around 40 countries). A variety of specifications were tried and those presented here had the best fit (using AIC, Akaike Information Criterion to decide among different specifications using the same observations). Independent variables which were not significant and whose inclusion worsened the overall fit, were removed.

The initial results (summarized in tables 6, 7 and 8) are generally consistent with the literature on diet quality, although not all the independent variables are significant. Child stunting and women’s low BMI decrease as per capita calorie supply increases (significantly in both cases) and as diet diversity increases (significant for women but not children). Child wasting is not responsive to per capita calorie supply but decreases significantly as diet diversity increases. Wasting tends to reflect recent factors (e.g. seasonal hunger or epidemics) more sensitively than does stunting. The diet diversity variable may reflect circumstances at time of collection of anthropometric data, while calorie availability represents an annual average.

Women’s and children’s overweight is positively associated with per capita calorie supply (unsurprisingly) and also with dietary diversity (MDD and MDD-W), although not significantly. This latter finding is consistent with Herforth et al. (2020) who cite two previous studies noting the positive association between dietary energy intake with dietary diversity. The coefficients on the GDRS sub-scores (NCD-Protect and NCD-Risk) have the expected sign for women’s overweight but are not significant. There are regional differences, in particular the Southeast Asia region has significantly higher stunting and wasting for children and low BMI for women, controlling for other factors (compared to the Africa region). The Eastern Mediterranean region has significantly more overweight both in children and women, controlling for other variables (compared to the Africa region). The Gini coefficient, a measure of inequality, is not significant in any of the regressions. The effect of calorie supply per capita is non-linear and has the strongest impact at the lower levels of calorie availability.

Results for hypertension and diabetes are mixed, perhaps because the data disadvantages mentioned above are more severe (less consistency of date, lack of age cohort data, and inconsistencies in the population covered, e.g. dependent variables are for all adults whereas some of the independent variables are only for women, etc.). Hypertension and diabetes both go down as ln(per capita calorie supply) increases and (results not presented) average level of hypertension is highest in low income countries and decreases consistently from low to lower-middle to upper-middle to high income countries. In theory this variable is supposed to 12