The and concise in its findings. The first

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 emissions3.  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.”3 I found all of the information 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 how a good scientific study is supposed to be presented 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 2.  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.  So, the study has a contrived set of individuals.  The data collected was also quite old, from a study done in the 1990s, which means their diet could be different from the current general population. Another data set was collected from a food frequency questionnaire that was set to estimate the consumption of 130 food items over 12 months, which resulted in steady data collection.1A 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 calculating GHG emissions, which analyzed 130 food items form UK food consumption tables1, weighted by kgCO2e per 100 grams of food.  This method was adapted from another study, investigating carbon taxes on foods in the UK1. 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.  In this study they didn’t have every single food item consumed 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 looked over, which could cause miscalculations.  This causes multiple estimations to have the possibility of having misconstrued data.  What if a chocolate powder had an equal amount of GHGs as an eight ounce steak?  It would be inconclusive because the ingredients within the chocolate powder were estimated. The fourth method used in this study was the standardization of the 2,000 kcal diet as an experimental control.  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 studies1.The fifth and final method used was the basic math calculation of GHG emissions through standard deviations of diet group, sex, and age, with 10 year age bands.  The significance was tested at a 0.05 level, 5%, based on StataCorp1. In analyzing the data, it is seen that the diet group with the highest GHG emissions was the high meat-eating men group, and the diet group with the lowest GHG emissions was the vegan women group.  Based on the ANOVA analysis there was a significant difference of 0.0001, in GHG emissions for the dietary groups that consumed animal products. On average, a meat based diet had 2.5 times more GHG emissions than that of a vegan diet1.  Not only did most participants produce lower gas emissions they were overall healthier.  This study showed that if one reduced meat consumption in their diet it would benefit climate change and have an overall reduction in GHG emissions. This is the first study that breaks down the differences in GHG emissions per diet, and while there are similar studies this is the only one to show the actual percentages and numbers. Similar studies that have dissected climatic change such are: Vieux F, Darmon N, Touazi D, Soler L. Greenhouse gas emissions of self-selected individual diets in France: changing the diet structure or consuming less? Ecol Econ (2012) 75:91–101 and Masset G, Vieux F, Verger EO, Soler L-G, Touazi D, Darmon N. Reducing energy intake and energy density for a sustainable diet: a study based on self-selected diets in French adults. American Journal of Clinical Nutrition. 2014;99(6):1460–1469.Lastly, a specific procedure I didn’t understand was the estimation of recipe GHG emissions.  The article explained that an estimation using percentages was used, but they don’t give provide any formulas, nor the ingredients with the estimations.  I would need a mathematical college course to help me in this situation to be able to formulate my own formula until I was provided with the one actually used.  Another major factor I didn’t fully comprehend was the use of kgCO2, greenhouse gas emissions in kilograms of carbon dioxide equivalents per day. I understand that certain foods produce these gases, however I would like to understand the environmental impact, and how these gases affect the earth.  I would have to actually take a class to comprehend and understand how GHG emissions harm the planet, and what measures can be taken to reduce anymore damage.

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