Abstract
Meat consumption patterns worldwide have dramatically changed over the past 50 years, putting pressure on the environment and leading—especially in industrialised and emerging countries—to unbalanced diets. Given demographic projections and foresight reports, the question is raised whether there are limits to the meat consumption. Based on data from 120 countries, this article analyses the evolution of meat consumption in general and the relationship between meat consumption and income in particular. The study shows evidence for an inverted U-shaped relationship between meat consumption and income, meaning that – at a certain level of income – average meat consumption will stagnate or even decline. The results can help policy makers to develop incentives for both environmental and health policies and offers stakeholders opportunities for further research and innovation.
Generated Summary
This study examines the evolving patterns of meat consumption worldwide, particularly focusing on the relationship between income and meat consumption. Using data from 120 countries, the research investigates whether there is an inverted U-shaped relationship between meat consumption and income, indicating a potential for meat consumption to stabilize or even decline at higher income levels. The study employs regression analysis to model the relationship, controlling for fixed effects and geographical area, culture, and trade. The key hypothesis is that meat consumption will stagnate or decrease after a certain GDP threshold is reached. The analysis uses various models, including pooled ordinary least squares (OLS), random effects, and fixed effects estimators, to assess the robustness of the findings. The research aims to contribute to both environmental and health policies by providing insights into consumer behavior and the factors influencing meat consumption.
Key Findings & Statistics
- The study uses data from 120 countries over the period 1961-2007.
- Meat consumption in developing countries may increase from an average of 10 kg per capita in the 1960s to a projected 37 kg by 2030, while consumption in developed countries may remain stagnant.
- EU statistics report daily protein consumption between 0.8 and 1.25 g/kg body weight for adults.
- The Willett diet, including 10 g beef, 10 g pork, 47 g chicken and eggs, and 23 g fish per person per day, could reduce the area of arable land by 10% and the area of grassland by 40% compared to FAO projections.
- According to FAO projections, meat consumption in developing countries may increase from an average annual per capita consumption of 10 kg in the 1960s to 26 kg in 2000, reaching 37 kg around the year 2030.
- The study uses panel data for 120 countries in the period 1970-2007 to analyze the link between meat consumption and income, while controlling for fixed effects and geographical area, culture, and trade.
- The turning point in income, where meat consumption starts to decline, lies between 32,000 and 55,000 US dollars (current) or between 35,000 and 53,000 constant 2005 international dollars, depending on the model.
- For countries below the turning point, meat consumption increases with 0.3% if income increases with 1% when GDP is expressed in current US dollars, while it increases with 0.5% when GDP is expressed in PPP terms.
- For countries above the income turning point, meat consumption decreases with 1.2% if income increases with 1% when GDP is expressed in PPP terms.
- The average meat consumption in China almost tripled in this period, up to a consumption of 53 kg/cap in 2007.
- In France, there is a decreasing trend, observed since the beginning of this century.
- Meat consumption in Brazil has increased from 40 kg/cap/year in 1980 to over 80 kg/cap/year in 2007.
- The average meat consumption in Japan increases slowly and remains below 50 kg/cap/year.
- Figures for African countries suggest broad differences in meat consumption across the continent, with 5 kg/cap/year in Burundi, around 10 kg/cap/year in Cameroon and Senegal and almost 50 kg/cap/year in South Africa.
Other Important Findings
- The study found evidence for an inverted U-shaped relationship between meat consumption and income, suggesting that at a certain income level, meat consumption will stagnate or decline.
- There is a positive relation between education level of the household head and reduced meat consumption.
- The research indicates the need for more interdisciplinary research and improved cooperation between environmental and health policy in industrialized and emerging countries, as well as developing countries.
- The share of Muslims in the population (REGMUS) was highly correlated with the share of other religions (REGOTH).
- Higher shares of Christians in a country corresponds to higher meat consumption ceteris paribus.
- In countries with a higher share of the population adhering Eastern religions (Hindu, Buddhists, etc.) meat consumption is significantly lower.
- There is a positive correlation between the masculinity index (MI) and meat consumption, but the significance of the variable depends on the specification used.
- The coefficients of the variable TRADE which measures the country’s openness, is only in a few specifications significantly different from zero.
- The majority of developing countries will only reach the turning point in the very long run.
Limitations Noted in the Document
- The study acknowledges that data from household-level surveys on diets would ideally be used, but such data is scarce and does not allow for identifying trends. Therefore, the study uses FAO Food Balance Sheets (FBS), which may overestimate consumption.
- The study does not control for the impact of meat price on meat consumption due to the unavailability of a worldwide meat price index.
- The study does not control for food crises because health scares only have a local and short-term impact.
- The number of observations included in the different regression specifications changes considerably due to data availability.
- The strict exogeneity assumption is not met for the TRADE variable when GDP is expressed in current US dollars.
Conclusion
The study provides robust evidence supporting an inverted U-shaped relationship between meat consumption and income, a critical finding that suggests a potential for reduced meat consumption in wealthier nations. The turning point, where meat consumption may start to decline, is estimated to occur at a specific income threshold, implying that economic growth alone does not necessarily lead to unlimited increases in meat consumption. This insight is crucial for policymakers, suggesting that economic development strategies can be designed to include interventions that encourage more sustainable dietary choices. The findings also highlight the complex interplay of factors influencing meat consumption, including cultural and religious differences. The research suggests that the establishment of new reference frameworks and policy benchmarking, perhaps driven by health concerns, could accelerate a shift towards reduced meat consumption. The study’s conclusions emphasize the need for collaborative efforts between environmental and health policies in both developed and developing countries to promote sustainable food systems. This is particularly relevant as livestock production is a significant contributor to greenhouse gas emissions, and shifting diets has the potential to mitigate these impacts. The study underscores the potential for a second nutrition transition, where plant-based foods become more prominent, thus aligning with the need for sustainable and healthy diets. The insights from this research call for further interdisciplinary investigations, with a strong emphasis on the development of targeted policies and initiatives that can positively influence meat consumption patterns globally. The impact of local cultural and religious values on consumer behavior must also be considered. Moreover, the establishment of a new reference framework and policy benchmarking might lead to a situation in which these countries will never reach a per capita meat consumption as the more developed countries in our dataset.