Discussion
This investigation provides evidence, for the first time to our knowledge, on how differences in personal income and food prices might jointly influence dietary intakes of key foods among men and women of diverse ages across both rich and poor countries. We found that income elasticities commonly varied by food category, region, age, and sex; in some cases considerably so, and in other instances, much less. For instance, an increase in income was estimated to increase fruit intake most strongly in SSA and globally in older women compared with younger men, and to increase processed meat intake in young men in SSA, but less so or not at all in older adults, women, or in other regions. Other foods (eg, red meat and fruit juice) had more consistent positive income elasticities across regions, ages, and sexes. We also identified evidence that intake of some food categories actually declines with rising income in certain regions and for certain demographic groups, such as beans/legumes in MENA/South Asia, Asia, and HIC, especially among older adults, and sugar-sweetened beverages among older adults in richer regions.
We identified evidence of varying influence of price on food intake. This included price sensitivity for fruits and whole grains in certain regions (eg, SSA, LAC, and FCP), but not others (eg, MENA/South Asia and HIC); small price sensitivity for vegetables, beans/legumes, nuts/seeds, and unprocessed red meat, with relatively higher sensitivity in young adults for unprocessed red meat; and consistent price sensitivity for fish globally. Among beverages, milk and fruit juice intake appeared consistently price responsive, with generally strongest effects in Asia; except for fruit juice in HIC which showed little price responsiveness. Sugar-sweetened beverage intake was price sensitive but highly variable, with the weakest effects among younger adults in LAC. Finally we found that most foods were less responsive to both income and price as national income increased, except for fruits and milk, which were also responsive at higher national income.
How do our findings compare to previous studies? Given the level of aggregation in prior studies, exact comparisons are not straightforward. We do find important similarities, however, even though many prior studies used expenditure or disappearance data. For instance, the relative higher responsiveness of SSA and lower income countries to income changes is consistent with previous findings.8 13 But overall, our income elasticities are lower on average, particularly for high-income countries. This may reflect that at higher income levels, an increase in income results in increased demand for quality rather than quantity. Own-price elasticities are more comparable for some groups. For instance, our estimates for fish (−0.4 to −1.0) generally fall within the confidence intervals reported in prior studies.11 12 The main differences in results are that (1) we found more goods that exhibited declining intake in response to rising incomes (ie, inferior goods), (2) we found fewer statistically significant relationships for a large number of food categories, particularly in higher income regions, and (3) whereas in prior studies, income and price elasticities mostly decrease with national income, we identified intake categories where this was not the case (eg, fruit intake in response to income changes, and milk intake in response to price changes).
Increasing the affordability of healthful foods has been considered a key strategy for national and international organisations.20 Our findings suggest that increasing income and/or reducing prices would likely increase fruit intake globally, but would have distinct benefits for men and women of all ages and across most countries, with potentially stronger effects of lower prices in certain regions and among younger men, and of higher income among older women. The latter results are consistent with within-country evaluations in which age positively correlates with nutritional knowledge and better diet choices, and in which women are more likely than men to make healthier dietary purchases with additional income.21 22 In contrast to fruits, our results suggest that vegetable intake may not significantly increase with higher incomes, and that intake of some plant-based foods (beans/legumes, nuts/seeds) might actually decrease in some regions. Beans/legumes may plausibly be considered an inferior good in many parts of the world, particular when considered by people as a protein source.
Our findings for nuts/seeds deserve some consideration. Peanuts make up the largest share of global nut availability at 4.5 kg/year/person (almonds, the leading tree nut, contribute only 0.12 kg/year/person).23 Thus, while in Western nations (the leading tree-nut consumers) many consider tree nuts as a relative luxury good, our findings largely reflect global peanut consumption patterns, driven by leading peanut consuming countries such as China, India, Indonesia, Nigeria, and Vietnam.23 In these nations, peanuts may be viewed as a traditional (and inferior) good by the public in contrast to the small amounts of tree nuts consumed in Western countries, which we could not separately evaluate. In other work it has been shown that increases in tree nut consumption positively correlate with education and income in the US.24
Our income-elasticity estimates suggest that income growth is likely to cause an increase in intake of unprocessed red meat globally, and in processed meats in SSA (especially among younger men), with little or no change in plant-based intake, other than fruit, and potential declines in beans/legumes and nuts/seeds (peanuts). While higher income allows for more food purchases, it also worsens certain dietary choices. For example, it is associated with greater demand for food away from home; a greater demand for more convenient, prepared and processed food due to additional time spent working; and a shift toward multi-national food products (considered and marketed as desirable) and away from traditional diets (often viewed as linked to less prestige and prosperity in developing nations).25 In Brazil, for instance, economic growth has coincided with steady trends toward ultra-processed, ready-to-eat foods of low nutritional value and away from minimally processed, plant-based foods.26 Our income-elasticity results suggest that further economic growth and prosperity alone may not improve dietary habits in many nations, and in fact will likely worsen certain aspects of the diet. This is consistent with global analyses of time trends in dietary patterns from 1990 to 2010, a period of general economic growth, which indicate that while middle-income countries modestly increased their intakes of healthful foods, unhealthy foods increased substantially more; whereas in some of the poorest countries, unhealthy foods increased while healthful foods decreased.10 These complex relationships between rising income and dietary habits likely explain, at least in part, the growing epidemics of obesity, diabetes, and other NCDs in many nations.
While all age groups appeared responsive to higher sugar-sweetened beverage prices (eg, as could occur from taxes, like those recently implemented in Mexico, the UK, and South Africa), young adults often appeared less responsive than older adults, especially in Latin America and the Caribbean. These findings imply that such policies could result in smaller effects at younger ages. Thus while relevant reductions might still occur, additional adjunctive strategies will likely be needed to reduce sugar-sweetened beverage intake by younger adults. Conversely, younger adults (and of course adolescents) often have the lowest incomes, which could partly or fully offset any reduced income sensitivity due to age alone.
Our findings highlight the need for combining economic development programs with policy approaches to improve diets. A number of population-based approaches have been found to produce desired outcomes. Some examples are media and educational campaigns aimed at either promoting healthy foods like fruits and vegetables or reducing intake of unhealthy foods high in sodium, sugar, and saturated fats; comprehensive school- and work-based interventions; direct regulation; and taxation of unhealthy foods or subsidies for healthy foods.27–29
Our analysis has several strengths. While relationships between income, prices, and food choice have been studied, combining GDD, World Bank, and ICP data allowed for a global coverage rarely seen in food and nutrition research, allowing for comparisons across individuals in rich and poor countries. Our data on dietary intakes permit evaluation of food consumption that may be notably more accurate than national availability estimates based on agricultural production, exports, and imports,9 and for the first time to our knowledge, allow investigation of global elasticities by age and sex.
Potential limitations should be considered. Dietary intake data are by nature imperfect and may be less accurate in certain regions; we accounted for uncertainty in our modelling, which led to wider confidence intervals and to lower statistical power (making it difficult to detect weaker associations). We modelled average effects and the response of any single individual to differences in price or income may vary. We considered 11 major food categories with available global dietary data; other foods relevant for health could not be considered. We did not evaluate cross-price elasticities for individual foods, although the modelling framework implicitly accounted for the cross-price effect of all other foods in aggregate. Our modelling cannot prove causality of income and price changes on intakes, and thus our findings should be interpreted cautiously when informing interventions and evaluations. Other factors, such as education and nutritional knowledge that were not available globally, may correlate with income and may separately influence diet.30 Educational attainment and income are, however, highly correlated at the national level, and thus the income variable may represent both purchasing power and other affluence-related variables. In this context, our results could be interpreted as the effects of affluence or economic prosperity more generally.
Furthermore, our results are based on cross-sectional analysis and should be interpreted with caution when considering income growth over time. The invariability of price and income across demographic subgroups ignores differences within countries and may have affected results, although we address this issue, in part, with age and sex variable interactions. Results were also affected by the use of representative prices for food categories not explicitly defined in the ICP (beans/legumes, nuts/seeds, sugar-sweetened beverages, and fruit juice). However, we did find evidence of high correlation between sugar and sugar-sweetened beverage prices, and fresh fruit and fruit juice prices for the US. Lastly, our choice of presenting findings by world region does not preclude sub-regional or country-level analysis; there may be important differences across countries that can be explored in future research.
In conclusion, our results provide novel global evidence for relationships of income and food prices with intakes of key food categories by region, age and sex. Several of the observed relationships appear to represent deeper preferences for specific foods, which can assist policymakers as they consider how economic incentives linked to income and price can be leveraged to tackle nutrition and health challenges. These findings can help inform strategies that counter worsening diets that tend to accompany economic development and make food prices reflect the total health and societal costs of food intake.
