Health-environment efficiency of diets shows nonlinear trends over 1990-2011

Abstract

Understanding the impacts of diets on health and the environment, as well as their association with socio-economic development, is key to operationalize and monitor food systems shifts. Here we propose a health-environment efficiency indicator defined as a ratio of health benefits and four key food-related environmental impacts (greenhouse gas emissions, scarcity-weighted water withdrawal, acidifying and eutrophying emissions) to assess how diets have performed in supporting healthy lives in relation to environmental pollution and resource consumption across 195 countries from 1990 to 2011. We find that the health-environment efficiency of each environmental input follows a nonlinear path along the Socio-Demographic Index gradient representing different development levels. Health-environment efficiency first increases thanks to the elimination of child and maternal malnutrition through greater food supply, then decreases driven by additional environmental impacts from a shift to animal products, and finally shows a slow growth in some developed countries again as they shift towards healthier diets.

Fig. 1. Environmental impacts and health loss of food supply in all countries at different levels of development.

a–e, GHG emissions (a), water withdrawal (b), acidification (c), eutrophying emissions (d) and DALYs per million people in natural logged form (e). In a–d, bar charts represent average environmental impacts per country and SDI level, while the grey points represent the life-cycle environmental impact of per capita daily diets in each country. Source data

Fig. 2. Change of dietary efficiency along socio-economic development.

a–e, Total efficiency (a), efficiency for GHG emissions (b), efficiency for water withdrawal (c), efficiency for acidifying emissions (d) and efficiency for eutrophying emissions (e). The points show the coordination of (SDI, efficiency) for each country and year, while the red lines in b–e show the fitted cubic function based on the regression analysis. The coloured points in a show the trend of some countries at different stages. The detailed regression analysis for the fitted function are included in Supplementary Tables 1–4. Source data

Fig. 3. Temporal change of DALY and environmental impacts in selected countries.

The value of each point connected by the lines is calculated as the ratio to the corresponding factor (DALY or environmental impacts) in the base year. Data are not available for all the countries during the time period 1990–2011 (for example, the statistics are lacking in 1990 for the Russian Federation) and thus present absence in some cases. Source data