The purpose of this study was to show how dietary greenhouse gas emissions varied by diet, specifically in the United Kingdom. It was a experimental research study done to estimate the differences between a meat-eater, fish-eater, vegetarian, and vegan diet, explicitly through greenhouse gas emissions in kilograms of carbon dioxide equivalents per day (kgCO2e/day). The 2,000 kcal diet was monitored as the independent variable, while the dependent variable was the greenhouse gas emissions emitted for all six diets.
The results obtained showed that an overall diet consisting of animal products generally had higher greenhouse gas (GHG) emissions, approximately 50% more carbon dioxide produced, than that of plant-based diets. In kilograms of carbon dioxide equivalents per day (kgCO2e/day) for high meat-eaters were an average of 7.19, for medium meat-eaters were 5.
63, for low meat-eaters were 4.67, for fish-eaters were 3.91, for vegetarians were 3.
81, and for vegans were 2.89**. The data shows that dietary GHG emissions for self-selected meat-eaters are nearly double than those of vegans, which indicates that a reduction in meat consumption inevitably would lower GHG emissions. The main reason why I chose to research this topic and why it fascinates me, is mainly based on the fact that our society has convinced us that animal agriculture, which fuels meat consumption, is not responsible for most of our greenhouse gases. When in fact, numerous studies has proven that livestock and the byproducts that come along with it are responsible for approximately 51% of all worldwide GHG emissions**.
Along with that, I find it interesting that livestock is blameworthy “for 65% of all human-related emissions of nitrous oxide– a greenhouse gas with 296 times the global warming potential of carbon dioxide.” ** I found all of that information is very interesting, but I had to see the application and actual data.Upon reading and dissecting the article I believe that this is an example of a good scientific study because it is clear and concise in its findings. The first method used was finding subjects and constructing a study design. The subjects collected were participants from the EPIC-Oxford cohort, which is a component of the University of Oxford, who are mainly vegetarian**. Other participants were found through “collaborating” practitioners, health food magazines, as well as vegetarian and vegan societies, while others were brought in by friends and family. The sample size comprised of 29,589 meat-eaters (high, medium, low), 8,123 fish-eaters (pescatarians), 15,751 vegetarians, and 2,041 vegans, which is a grand total of 55,504 participants having a final dataset of 12,666 males and 42,848 females between 20-79 years of age.
The study seems to have an adequate sample size considering it’s more than 30, however the ratio of males to females is essentially 1:3; at the same time however, one doesn’t know the diet of every female or male which helps in randomizing the data. Considering however that some participants were recruited by friends and family, there’s a chance that they have similar diets, which could cause the data to be biased. The data collected was from a food frequency questionnaire that was set to estimate the consumption of 130 food items over 12 months**. A second method used was for classifying the six diet groups. The high meat-eaters were those who consumed more or equal to 100 grams of meat a day, medium meat-eaters consumed 50 to 99 grams of meat per day, low meat-eaters consumed 0 to 50 grams of meat per day, pescitarians, vegetarians, and vegans. Initially I loved this categorization method, however a breakdown of various meats (beef, pork, etc.) would have been helpful, for each animal produces a different amount of GHG emissions.The third method used was for actually calculating GHG emissions, which analyzed 130 food items form UK food consumption tables**, weighted by kgCO2e per 100 grams of food.
This method was adapted from another study, investigating carbon taxes on foods in the UK**. A food balance sheet from the Food and Agriculture Organization from 2013 was also used, and I thought that this form of data collection was useful but came short. Not every single food item is in the provided appendix, so they constructed an ‘adjustment for density’ algorithm to be used for the following: cheese, fruit juice, dried fruit, soy milk, etc.. How else would one count a GHG emission for something like a pinch of salt? Similarly, the way the participants went about their cooking processes it is impossible to know what cooking methods were used. Also, largely processed foods were not a part of the food balance sheet, so some recipes were estimated and calculated by only a single researcher and later double checked by the entire team.
This causes multiple estimations to have the possibility of being misconstrued. What if a chocolate powder has an equal amount of GHGs as an eight ounce steak? It is inconclusive because for the chocolate powder certain things were estimated. The fourth method used in this study was the standardization of the 2,000 kcal diet, which is also used in the United States. The use of the standard diet was innovative, for it would limit any form of energy consumption differences. The limitation of under and over eating reporting would also be cut off with this method, which is reportedly overseen in dietary studies.
The fifth and final method used was the basic math calculation of GHG emissions through standard deviations of diet group, sex, and age, through 10 year age bands. The significance was tested at a 0.05 level, 5%, based on StataCorp**. In analyzing the data it is seen that the diet group with the highest GHG emissions was the high meat-eating group, and the diet group with the lowest GHG emissions was the vegan group.