I converted Brian Tomasik’s How Much Direct Suffering Is Caused by Various Animal Foods? to Guesstimate . We now have ranges, distributions, and the sensitivity analysis to draw on to refine the estimates. I also added two columns to determine the suffering of the average per capita consumption, which seems to me like the more intuitive figure; refined the estimates with additional research; and added organic eggs for comparison.

Brian Tomasik’s classic “How Much Direct Suffering Is Caused by Various Animal Foods?” investigates the most easily observable suffering footprint of various products derived from animal products.

The page, in it’s latest incarnation, contains a JavaScript calculator for putting in one’s own values. But I’ve gotten used to using ranges and having a sensitivity analysis to draw on to decide which cells to research further. So I transferred Brian’s model to Guesstimate, mostly drawing on his research but also adding some of my own when I couldn’t decide what the variance should look like.

Finally, I’ve also added some more data points to it:

I researched the average consumption (in the US). People tend to think in portions rather than in kg, and they tend to think in terms of cutting out animal products rather than reducing their consumption by an absolute delta. The new suffering times average consumption column greatly reduces the gap between beef and milk because people tend to consume so much milk, and it makes chicken meat worse than eggs because people tend to consume so much chicken meat. I’ve added a row for organic eggs. I’ve often been asked how organic eggs stack up against battery cage eggs (or even more ambiguously, how aviary system eggs stack up). I never knew, because while the conditions are arguably better, the chickens used are usually not Leghorns, so they produce fewer eggs per year and at more steeply declining rates so that they’re killed earlier. Therefore, more chickens are needed to satisfy the same demand. I still don’t know – my estimate is much to close and unreliable for that – but it looks like organic eggs fare a bit better. The difference is less than even just one order of magnitude at the moment, so expect it to change when you touch some of the more sensitive inputs.

In 2014, Brian added some reservations to his article:

I’m somewhat less gung-ho about these numbers than when I first wrote this piece because in practice, the side effects of meat consumption on wild animals and Earth’s long-run future probably matter much more than the (horrific) direct impacts on farm animals themselves. Of course, evaluating the net impact of these indirect side effects is much trickier. Whatever the sign is of the indirect effects, indirect effects should be more similar across animals than the suffering figures are across animals, since cows and chickens don’t differ as much in their environmental impacts as in their direct suffering per kilogram. Hence, these neglected factors should tend to drive the (absolute value of the) ratios of per-kilogram impact estimates across species closer toward 1.

Read The Importance of Wild-Animal Suffering for more information.

Most of the considerations are not mine but Brian’s and ACE’s (Dairy/Eggs AYLA and AEPY , Meat Land Animal Equivalents Per Person Per Year, Leafleting Impact Calculator), so check out their work for more guidance. (I’ve also usually linked and copied their summaries into the Guesstimate cells.)

I’ve been reading various different figures on the average lifespans of Leghorns. These chickens can of course live many years, but they produce most eggs in their youth, their first year, and then fewer and fewer with every further year. Therefore, their average age at death is determined by a calculation that probably involves the monetary value of their meat, rent, and the price of new pullets. The age that makes for the most profitable killing may be different between countries.

Brian’s Canadian source (before 2007 and perhaps before 2000 judging by the dates of the sources) indicates that they live for around 500 days and lay 288 eggs p.h. p.a. (per hen per year). Norwood and Lusk (2011) write, “Cage eggs are assumed to be white eggs from a White Leghorn type breed. This hen will produce 509 eggs throughout its 2.21 years of life.” So around 800 days at 230 eggs p.h. p.a. ACE ’s analysis of the USDA statistics from 2012 and 2014 indicates that they live around 412 to 515 days. My different approach to almost the same data (I only have access to the 2012 statistics) puts the average age at 602 to 634 days (at 271–274 eggs p.h. p.a.).

I discount Brian’s source only because it’s Canadian and over a decade old, so the economic conditions were surely different enough to explain the difference. Norwood and Lusk have their own university farms where they may allow their chickens to get older than they usually do; their figure is the highest of all. I rely most on the USDA statistics and there on my reanalysis.

Some data points:

Bovine enthusiast: 5–6 years University of Illinois: “The typical cow remains in the milking herd less than 4 years even though peak milk production related to maturity ordinarily does not decline until 8 or 9 years of age.” Cited by Wikipedia as evidence for a lifespan of four years, but the author probably intended 4 + (1 to 2) years because the cow as to grow up first before she can produce milk. (Does someone want to correct it?) Brian: Alberta Milk (n.d.): “The typical dairy cow lives an average of five years, with the first two years focused on providing a strong foundation for the healthy development of the cow. From age two, the mature cow will become a productive member of the milking herd (meaning, she will produce milk).” Penn State indicates that conception happens at around 15 months Virginia Tech implies that calves are born for the first time at 24 months.

Most confusion seems to stem from the time the cow has to grow up before she can be artificially impregnated by the farmer, and then the time that her child grows up in utero before lactation starts. But there are still differences of three to four years even so. The result is not very sensitive to this input, so I haven’t researched it further, but if someone know what the most reliable data are, then I’d love to adapt the Guesstimate!

For the sentience multipliers – numbers from the interval [0.0, 1.0] – I opted for something that captured my conflicting intuitions about sentience and looked properly arbitrary at the same time so not to signal sophistication where there is none. The formulae ended up looking like =max(0, 1-lognormal(2.5, 1)/100) . A log-normal distribution mirrored at a vertical axis so that it bulges up right before 1, and crudely tweaked so not to go below 0.

My intuitions are (1) that sentience may come in degrees, may reach different degrees for different individuals of the same species, may fluctuate for the same individual; (2) that experts disagree over the sentience of different species so that they have degrees of sentience with different probabilities; or (3) that people can legitimately have different opinions on the degree of sentience of an individual just as they can have differing opinions on how democratic each of the US, Switzerland, China, and North Korea are.

In each of these cases, my distributions mean different things, but the general shape seems to match all of them similarly well or badly.

Chickens farmed for meat are killed very young, after around six weeks, so they receive a slightly lower sentience distribution than chickens farmed for eggs, because I think I was less sentient as a child too. Fish like to cause little scientific kerfuffles (just search ACE ’s Research Library for “fish”) over whether they’re conscious or feel pain. Someone who has read this far is probably acquainted with expected value and will not use the possibility that fish might not suffer as an excuse to buy and eat them. That said, I was surprised by how sensitive the result was to this input. It still takes a probability of 0.0001 (or odds of 1:10,000) to press the expected suffering per kg for salmon to the level of milk, and there are probably nowhere nearly enough fish experts in the world to be sure at such an extreme level even if they all agreed, but as it is, the input is correlated with the result at r² = 0.58 (and looks correlated too in the scatter plot).

The suffering multipliers were somewhat informed by Dr. Sara Shields’ and Dr. Bailey Norwood’s estimates cited in Veganomics (and, for the latter, in Compassion, by the Pound).