Environmental impact of diets for dogs and cats

Abstract

Food production is responsible for almost one-quarter of the environmental impact and, therefore, its importance regarding sustainability should not be overlooked. The companion animal population is increasing, and an important part of pet food is composed of ingredients that have a high environmental impact. This study aimed to evaluate the impact of dry, wet, and homemade pet diets on greenhouse gas emission, land use, acidifying emission, eutrophying emissions, freshwater withdrawals, and stress-weighted water use. The wet diets were responsible for the highest impact, and dry diets were the type of diet that least impacted the environment, with a positive correlation between the metabolizable energy provided by animal ingredients and the environmental impact. It is necessary to consider the environmental impact of pet food since it is significant, and the population of pets tends to increase.

Full text

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Environmental impact of diets
for dogs and cats
Vivian Pedrinelli, Fabio A. Teixeira, Mariana R. Queiroz & Marcio A. Brunetto*
Food production is responsible for almost one-quarter of the environmental impact and, therefore,
its importance regarding sustainability should not be overlooked. The companion animal population
is increasing, and an important part of pet food is composed of ingredients that have a high
environmental impact. This study aimed to evaluate the impact of dry, wet, and homemade pet
diets on greenhouse gas emission, land use, acidifying emission, eutrophying emissions, freshwater
withdrawals, and stress-weighted water use. The wet diets were responsible for the highest impact,
and dry diets were the type of diet that least impacted the environment, with a positive correlation
between the metabolizable energy provided by animal ingredients and the environmental impact. It is
necessary to consider the environmental impact of pet food since it is signicant, and the population
of pets tends to increase.
Companion animals are considered part of the family, and their population is growing1. e three top countries
regarding canine population are the U.S. (76.8 mi dogs), Brazil (52.2 mi), and China (27.4 mi), and regarding
the feline population the top three countries are the U.S. (58.4 mi), China (53.1 mi), and Brazil (22.1 mi)2–4. In
Brazil, according to a nationwide census in 2013, the dog population has overcome the number of children2. is
expansion in the pet population increases the demand for products of this segment, including food5. Because pet
foods are rich in ingredients of animal origin, and this type of ingredient is known to be responsible for higher
gas emissions and land use6,7, it is important to consider their impact on the environment.
A meta-analysis on the impact of food, which included 38,700 farms and 119 countries, observed that food
production is responsible for 26% of total anthropogenic greenhouse gas emission (GHG)7. According to the
authors, animal production, including sh, is responsible for 31% of GHG, and crops are responsible for 27%.
e land use corresponds to 24% of emissions, of which 16% are related to animal production and 8% to crops.
e Food and Agriculture Organization (FAO) estimates that 50% of the habitable land and 70% of freshwater
withdrawals are used for agriculture8.
GHGs are gas substances that constitute the atmosphere and can be natural or anthropogenic, which absorb
radiation emitted by the terrestrial surface. ey prevent the loss of heat to space, keeping the terrestrial surface
potentially warmer and, therefore, can cause alterations to the atmosphere balance. Some of the GHGs are carbon
dioxide (CO2), methane (CH4), nitrous oxide (N2O), ozone (O3), and water vapor. e emission of carbon dioxide
equivalents (CO2eq) represents the mass of CO2 that causes the same radiative forcing of a determined GHG
mass over the same period and is a measure that comprehends all the GHGs9. For most of the foods, the highest
percentage of GHG emission results from the change in the soil, which is caused by deforestation and carbon
composition of the soil, along with fertilizers. Together, they can represent about 80% of the CO2eq of foods7,9,10.
Land use is another tool to estimate environmental impact. It is an important parameter to indicate if a
region can support the production of food. For example, livestock accounts globally for 77% of farming land
and produces only 37% of total protein7. Other indicators of environmental impact are acidifying emissions (as
sulfur dioxide equivalent emission), eutrophying emissions (as phosphate equivalent emissions), freshwater
withdrawals, and stress-weighted water use7.
Little is known regarding the impact of feeding canine and feline populations. A study11 observed that the
ecological footprint (or pawprint) of the Chinese population of dogs and cats is equivalent to 70 to 245 million
Chinese citizens, depending on the size of the animal and diet consumed. Another study conducted in Japan12
observed that the ecological pawprint of a dog can be similar to that of one Japanese citizen. In the U.S., a study13
observed that the canine population was responsible for between 25 and 30% of the animal production impact
regarding land use, water, and fossil fuels. A recent study14 estimated the global pawprint of pet food based on
dry diets from the U.S. and observed that pet food could be responsible for up to 2.9% of CO2eq emission and
up to 1.2% of agricultural land use. All of these studies, however, used dierent methods to evaluate the diet
composition, considering either hypothetical diets or only dry diets.
OPEN
School of Veterinary Medicine and Animal Science, University of Sao Paulo, Sao Paulo, Brazil. *email: mabrunetto@
usp.br
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erefore, the aim of this study was to evaluate the environmental impact of dierent types of diets for dogs
and cats in Brazil, since it is among the top countries regarding canine and feline population and is representative
in a global environmental impact scenario.
Results
Prole of diets. A total of 938 diets, 618 for dogs (316 commercial dry, 81 commercial wet, 139 commercial
homemade, and 82 homemade from websites) and 320 for cats (180 commercial dry, 104 commercial wet, 11
commercial homemade, and 26 homemade from websites) were included in the present study (see the sup-
plementary materials). A total of 212 ingredients were found at diet label or websites, of which 46.2% of animal
sources (n = 98/212) and 53.8% of vegetable sources (n = 114/212). Ingredients of commercial wet and dry diets
were 49.5% of animal sources (n = 47/95 ingredients listed) and 50.5% of vegetable sources (n = 48/95), whereas
the ingredients of homemade diets (commercial and website) were 45.3% of animal sources (n = 68/150 ingredi-
ents listed) and 54.7% of vegetable sources (n = 82/150). e ve most common ingredients in commercial dry
and wet diets were poultry by-product meal (used in 488 diets), poultry fat (in 478 diets), whole cornmeal (in
355 diets), broken rice (in 342 diets), and beet pulp (in 316 diets). e ve most common ingredients in com-
mercial or internet homemade diets were cooked carrot (in 134 diets), cooked squash (in 79 diets), cooked sweet
potato (in 77 diets), cooked zucchini (in 74 diets), and cooked chayote (in 73 diets) (TableS3).
Macronutrient prole. Dry diets for both dogs and cats presented the highest metabolizable energy
(kcal/g) (p < 0.001) and nitrogen-free extract (NFE) content (g/1000kcal) (p < 0.001). As for protein content
(g/1000kcal), wet diets for dogs presented the highest amounts, followed by homemade diets (p < 0.001), and wet
and website homemade diets for cats had the highest amounts (p < 0.001). Regarding fat content (g/1000kcal),
wet diets for dogs contained the highest amounts (p < 0.001), whereas for cats the wet diets were higher in fat
than dry diets (p < 0.001).
e prole for metabolizable energy, crude protein, crude fat, and nitrogen-free extract of each category of
diet for dogs can be observed in Fig.S1, and for cats in Fig.S2.
Nutrient and energy sources. e protein, fat, and metabolizable energy sources, whether of animal
or vegetable origin, were evaluated and the results are presented in TablesS1 and S2 and Fig.1. e median
percentages of protein and fat from animal origin were signicantly higher for all of the types of diets, for both
dogs (p < 0.001) and cats (p ≤ 0.03), and the metabolizable energy provided by animal ingredients was higher for
all diet types for cats (p < 0.001). e metabolizable energy provided by animal sources for dogs was only higher
for dry (p < 0.001) and wet diets (p < 0.001), with no dierence in commercial (p = 0.1) or website (p = 0.09)
homemade recipes.
Environmental impact estimate. For all of the variables of environmental impact evaluated, wet diets
represented a signicantly greater impact on the environment, for both dogs (Fig.2) and cats (Fig.3). In most
cases, dry diets were responsible for less environmental impact than the other types of diets. Regarding home-
made diets, the environmental impact was intermediary between wet and dry diets, except for acidifying emis-
sions, freshwater withdrawals, and stress-weighted water use in diets for cats, in which they were similar between
dry diets and commercial homemade diets.
To summarize the data set information and better explore the contributions of dierent diet variables evalu-
ated on the environmental impact parameters studied. Figure4 shows the results of the principal component
analysis (PCA) of diets for dogs, considering the rst (PC1) and second (PC2) principal components, responsible
for 71.9% of data variance for dogs (Fig.S3). For variables regarding diets for dogs, the metabolizable energy
was one of the characteristics that were most responsible for the horizontal dispersion of the data, followed by
sulfur oxide equivalent (SO2eq) and phosphate equivalent (PO43−eq). According to the results of the PCA, the
higher the metabolizable energy of animal origin, the higher the environmental impact measured with PO43-eq
and SO2eq. e variables that inuenced the vertical dispersion the most were the fat from both animal and
vegetable origin, followed by land use and CO2eq, which have the same direction as the vegetable fat, which
suggests that the higher the fat from vegetable origin, the higher the impact measured with CO2eq and land use,
and an inverse correlation with fat from animal origin. From the PC1, it can also be observed that metabolizable
energy, fat, and protein from vegetable origin, as well as NFE, had an inverse relationship with the variables of
environmental impact.
Wet diets were dierentiated from the other categories of diets and correlated to an increased environmental
impact (Fig.5).
Figure6 shows the results of the PCA of diets for cats, considering PC1 and PC2, responsible for 71.0% of
data variance for cats (Fig.S4). e results are very similar to those of diets for dogs, with a correlation between
the metabolizable energy of animal origin and the environmental impact measured with PO43-eq and SO2eq.
Regarding the PC1, as it was observed in dogs, the metabolizable energy, fat, and protein from vegetable sources,
as well as NFE, presented an inverse relationship with the variables of environmental impact.
Similar to dogs, the wet diets for cats correlated to an increased environmental impact, as the diet observations
follow the same direction as the vectors of the variables for environmental impact (Fig.7).
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Discussion
In the present study, extensive research regarding the composition of dierent types of pet food was performed
to estimate the environmental impact of diets for dogs and cats in Brazil. is approach allowed to estimate the
Figure1. Boxplots of the distribution of percentages of crude protein, crude fat, and amount of metabolizable
energy provided by either animal or vegetable origin for each type of diet. Diet category: Cc homemade diets,
Cs website homemade diets, S dry diets, and U wet diets. Plots of the same variable that have dierent letters
diered (p < 0.05) according to the multiple comparison test between groups.
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impact of dierent variables of environmental impact, which revealed that wet diets positively correlated to
higher environmental impact than dry or homemade diets.
Figure2. Boxplots of the estimated environmental impact per 1000kcal of diets for dogs according to the type
of diet for the variables carbon dioxide equivalent emission, land use, acidifying emission, eutrophying emission,
freshwater withdrawal, and stress-weighted water use. Plots of the same variable that have dierent letters
diered (p < 0.05) according to the multiple comparison test between groups. Diet category: Cc homemade diets,
Cs website homemade diets, S dry diets, and U wet diets. Plots of the same variable that have dierent letters
diered (p < 0.05) according to the multiple comparison test between groups.
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Figure3. Boxplots of the estimated environmental impact per 1000kcal of diets for dogs according to the type
of diet for the variables carbon dioxide equivalent emission, land use, acidifying emission, eutrophying emission,
freshwater withdrawal, and stress-weighted water use. Plots of the same variable that have dierent letters
diered (p < 0.05) according to the multiple comparison test between groups. Diet category: Cc homemade diets,
Cs website homemade diets, S dry diets, and U wet diets. Plots of the same variable that have dierent letters
diered (p < 0.05) according to the multiple comparison test between groups.
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If a 10kg dog with an average caloric intake of 534kcal per day15 is considered, we can estimate the yearly
consumption of calories and, therefore, can estimate the annual environmental impact. If we consider the results
of the present study, the median of CO2eq of a dry diet per 1000kcal is 4.25kg and a wet diet of 33.56kg. is
average dog would be responsible for 828.37kg of CO2eq per year if consuming dry diets or 6,541kg of CO2eq
per year if consuming wet diets. is is consistent with 12.4 to 97.8% of the emission of a Brazilian citizen, which
is 6.69 tCO2eq per year16. If we extrapolate this emission to the canine population in Brazil, of 52.2 million (2),
the total emission would be between 0.04 and 0.34 Gt CO2eq per year, which would represent from 2.9 to 24.6%
of the total estimated emission of 1.38 Gt for Brazil16. ese results bring to light the importance of the role of
pet food in the discussion of sustainability since its impact can be extensive.
In the present study, it was observed that dry pet foods caused lower environmental impact because the
environmental impact variables studied (all variables for dogs and CO2eq, land use, and PO43− eq for cats) were
lower per 1000kcal. However, the number of veterinarians, breeders and pet owners interested in homemade or
home-prepared diets seems to be increasing17–20. Our data showed, however, that this type of diet is related to a
higher environmental impact than conventional dry diets. Wet diets, whilst indicated as a strategy to increase
palatability and water consumption by cat and dogs with a higher risk of developing urolithiasis21,22, were the
ones that had the highest environmental impact.
Many factors can inuence the sustainability of food, including ingredient choice, ingredient composition,
digestibility, and percentage of ingredient inclusion. Sometimes the ingredient choice is made taking into consid-
eration consumer demand instead of only nutritional composition, which can lead to ingredients that compete
directly with human diets. Furthermore, diets are sometimes formulated to contain an excess of nutrients. ese
factors represent a challenge to optimize the sustainability of pet food5.
In the subject of sustainability of the pet food system, animal protein is almost always in the spotlight. Animal
proteins usually have higher CO2eq emissions than proteins from vegetables. For example, the production of
100g of pea protein is responsible for the emission of 0.4kg CO2eq, while the production of the same amount
of protein from beef is responsible for 35.0kg CO2eq, almost 90 times more7. Even when comparing the pea
farm with the highest carbon footprint (0.8kg CO2eq/100g protein) with the lowest farm of beef or chicken
production (9.0 and 2.4kg CO2eq/100g protein, respectively), there is an important dierence between plant-
and animal-based proteins. Human plant-based diets or diets with more plant-based protein require less energy,
less freshwater, and less land use when compared to diets with more ingredients of animal sources23. Dogs and
cats, however, have dierent nutritional requirements and are considered carnivores15,24 and, therefore, vegan
diets could lead to risks for these species25. Specically, about proteins requirements, synthetic amino acids can
Figure4. Principal component analysis (PCA) of rst principal component (PC1) versus second principal
component (PC2) of diets for dogs. ENN nitrogen-free extract, PBv protein from vegetable sources,
Emv metabolizable energy from vegetable sources, Eev fat from vegetable sources, CO2eq carbon dioxide
equivalent, area land use, PO4eq phosphate equivalent, SW stress-weighted water usage, SO2eq sulphur oxide
equivalent, UA freshwater withdrawals, PB protein content, EE fat content, Ema metabolizable energy from
animal sources, Pba protein from animal sources, Eea fat from animal sources.
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be added to pet foods as a way to correct possible nutritional imbalances24, but environmental impact of this
addition was not evaluated.
e present study observed that most of the proteins of the diets were from animal origin. Despite the intake
of vegetable proteins having a lower impact on the environment, in the case that animal protein needs to be
included the choice for production with lower impact is important. According to the Food and Agricultural
Organization (FAO), 61% of pork production, 81% of chicken production, and 86% of egg production use
intensive farming methods, which can reduce considerably the impact on the environment, especially regard-
ing land use and CO2eq emission26. In this case, products of extensive farming, especially those from pastures
from deforestation as occurs in most developing countries, can represent a higher impact, and therefore should
be avoided27. However, other studies showed that pasture development minimizes the environmental impact
of extensive farming due to pasture consumes part of the GHGs produced by animal production, and dierent
pasture management strategies can be eective alternative for sustainable animal protein production28,29.
Several ingredients used in pet food are considered by-products, and this could be considered as a factor
that reduces the impact of these foods5,13. According to the Brazilian Association of Animal Rendering30, ingre-
dients produced by rendering are named non-edible products of animal origin, which include meals, fats, and
blood derivates. According to a report from this institution, approximately 38% of beef, 20% of pork, and 19%
of chicken is viscera or blood that is not used for human consumption31. Of all the by-products produced in
Brazil, 12.8% are used in the pet food segment, and the rest is used for animal production, biodiesel, hygiene, and
cleaning, among other uses32. ere is no information on how much of these by-products are turned into meals
and fats and how much is used fresh, or even if the fresh oal is not considered in this calculation of rendering
potential. e argument that consuming by-product is more sustainable and therefore should not be considered
when estimating the environmental impact of pet food, however, can be partially true. Fresh oal can sometimes
compete with human markets and there may not be sucient by-products from the industry of human food to
feed the increasing population of pets, which means that animal production could need an increase due to pet
food demand32. In the present study, all types of diets contained by-products such as oal or meat meals, although
dry and wet diets presented by-products more oen than homemade diets.
e pet food industry should have diets that are accepted by the owners and at the same time be nutrition-
ally balanced and palatable for the pets. ere is no single strategy for improving sustainability that applies to
all manufacturers since regional demand and socioeconomic development must be taken into consideration5.
Suggestions to promote more sustainable pet food include the use of alternative protein sources. As protein-rich
ingredients can be one of the main sources of environmental impact, the choice of protein type is very important,
not only between vegetable or animal sources but among dierent species, such as beef, pork, chicken, or sh. e
dierent sources of protein have dierent impacts regarding sustainability7 and, therefore, a change of inclusion
or ingredient should be considered depending on the nutrient requirement and diet composition as a whole.
Figure5. Biplot of standardized rst (PC1) and second principal components (PC2) with observations of diets
for dogs. Cc homemade diets, Cs website homemade diets, S dry diets, U wet diets, ENN nitrogen-free extract,
PBv protein from vegetable sources, Emv metabolizable energy from vegetable sources, Eev fat from vegetable
sources, CO2eq carbon dioxide equivalent, area land use, PO4eq phosphate equivalent, SW stress-weighted
water usage, SO2eq sulphur oxide equivalent, UA freshwater withdrawals, PB protein content, EE fat content,
Ema metabolizable energy from animal sources, Pba protein from animal sources, Eea fat from animal sources.
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Furthermore, the inclusion of alternative ingredients, such as insects, could improve the sustainability of a diet.
e estimated CO2eq emission per 100g of protein from mealworms (Tenebrio molitor) is 14kg, and the use is
approximately 18 m2, which can be up to 14 times less than chicken, pork, or beef production33.
Another possibility of providing a more sustainable diet for pets is to avoid providing nutrients in excess.
Our data showed that diet with higher NFE caused lower environmental impact. e daily recommended intake
of protein according to FEDIAF15 per 1000kcal is 52.1g for inactive dogs and 83.3g for inactive cats, and the
daily recommendation for fat intake is 13.75g for inactive dogs and 22.5g for inactive cats. All types of diets
included in the present study provided more protein and fat than recommended for dogs and cats. Amino acids
provided by the extra protein are not stored in the organism and can either be utilized as an energy source or
be excreted. Fatty acids provided by excessive fat, on the other hand, are utilized as an energy source or stored
as fat deposits, which can lead to obesity24. is excessive intake of nutrients can be seen as a potential waste of
resources from a sustainable point of view5. However, sometimes higher protein and fat contents in diets can be
used to enhance the acceptance of diets by pets, and a balance should be thought between excessive nutrients
and palatability of the diet.
Materials and methods
Diet selection. To estimate the environmental impact, data was collected from dierent types of pet food
for healthy adults. All pet foods were categorized as dry (extruded pet food with 12% or less moisture), wet
(canned or pouch), and homemade diets (produced using the same ingredients as man food). Homemade pet
foods were subcategorized as "commercial homemade" (produced and sold by pet food companies) or "website
homemade" (recipes recommended by websites to be cooked at home by owners). To estimate the environmental
impact of commercial pet foods, all commercial dry and wet diets found on the websites of the three major retail-
ers of the pet food sector in Brazil were selected. Commercial homemade diets were selected aer a search using
the Google search tool using the Portuguese terms for “buy” and "homemade diet", followed by the terms “dog”,
“canine”, “cat” or “feline”. Website recipes published in Portuguese were selected using the Google search tool,
and search terms were “homemade diet recipe” and “homemade food recipe” followed by the terms “dog” and
“cat”. For both commercial and website homemade diets, the results obtained up to the 10th page of the search
tool for each term were considered.
All diets included were advertised as complete and balanced for healthy adults, and exclusion criteria were
diets for puppies or kittens, senior diets, therapeutic diets, and treats. Website homemade diet recipes were
Figure6. Principal component analysis (PCA) of rst principal component (PC1) versus second
principal component (PC2) of diets for cats. ENN nitrogen-free extract, PBv protein from vegetable origin,
Emv metabolizable energy from vegetable origin, Eev fat from vegetable origin, CO2eq carbon dioxide equivalent,
area land use, PO4eq phosphate equivalent, SW stress-weighted water usage, SO2eq sulphur oxide equivalent,
UA freshwater withdrawals, PB protein content, EE fat content, Ema metabolizable energy from animal sources,
Pba protein from animal sources, Eea fat from animal sources.
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excluded if the quantity of one or more ingredients was not specied and the same recipes on dierent websites
were also not included.
Ingredient inclusion percentage. Information regarding the ingredients (except premixes, additives,
and preservatives) and guaranteed analysis from labels of all commercial diets were collected. For the recipes of
homemade diets acquired from websites, the ingredients and their amounts were considered as described by the
website’s authors.
e ingredient inclusion percentages for each commercial diet were estimated using a diet formulation
soware34, aiming at the dry matter macronutrient concentration. e guaranteed analysis information of macro-
nutrients (crude protein, crude fat, crude ber, and ash) was converted to a dry matter basis according to the
moisture declared on the label. is information was then inserted into the nutrient composition part of each
diet in the soware.
For nutrients with minimum guaranteed levels (crude fat and crude protein), values for maximum inclusion
in the soware were considered as up to 10% of the minimum value. For nutrients with maximum guaranteed
levels (crude ber and ash), only maximum levels were inserted in the soware.
e ingredient database for commercial wet and dry diets was obtained preferably from the Brazilian Asso-
ciation of the Pet Food Industry (ABINPET)35, but when not described in this publication, other sources were
used36,37. For the homemade diets (commercial and website), the ingredient database was obtained from the
USDA’s FoodData Central37 or, when not presented at FoodData Central, the Brazilian Table of Food Composi-
tion (TACO)38 was used.
Aer the percentages of inclusion of ingredients were estimated in a dry matter basis, they were converted to
percentage of inclusion in original matter basis (as fed), considering the ingredients’ moisture35–37.
For the website homemade diet recipes, the amount in original matter basis was already stated, and inclusion
percentage was calculated according with total amount of the recipe and the amount of each ingredient.
Macronutrient prole. e quantities of protein, fat and nitrogen-free extract (NFE) of the diets were cal-
culated according to label information provided by the manufacturers. e information regarding the metabo-
lizable energy and the minimum amounts of crude protein and crude fat according to the guaranteed analysis
information were obtained, and with this information the amount of nutrient per 1000kcal of the diet was esti-
mated for the dry, wet, and commercial homemade diets. For these three types of diets, the NFE was calculated
according to the NRC24 equation:
Figure7. Biplot of standardized rst (PC1) and second principal components (PC2) with observations of diets
for cats. Cc homemade diets, Cs website homemade diets, S dry diets, U wet diets, ENN nitrogen-free extract,
PBv protein from vegetable sources, Emv metabolizable energy from vegetable sources, Eev fat from vegetable
sources, CO2eq carbon dioxide equivalent, area land use, PO4eq phosphate equivalent, SW stress-weighted
water usage, SO2eq sulphur oxide equivalent, UA freshwater withdrawals, PB protein content, EE fat content,
Ema metabolizable energy from animal sources, Pba protein from animal sources, Eea fat from animal sources.
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For the website homemade diets, the information was obtained by the composition of the recipe, as they did
not contain labels. According with the recipe, the metabolizable energy, protein, fat, and NFE were estimated
based on the composition of nutrients37.
e metabolizable energy of each diet as informed by the manufacturers on the labels was considered for
commercial dry, wet and homemade diets. e Atwater method was used to calculate the energy of website
homemade diets24, considering 4kcal per gram of protein and NFE and 9kcal per gram of fat39.
Nutrient and energy source estimate. To better understand the source of nutrients of diets for dogs and
cats, the percentage of protein, fat and metabolizable energy provided by vegetable or animal ingredients was
calculated for each diet. e percentage was calculated according to the contribution of the nutrient provided
by each ingredient in the diet, and if this ingredient was of animal or vegetable origin. For the calculation of the
energy source percentage, the energy provided by each ingredient type was considered.
Environmental impact estimate. e environmental impact variables evaluated were greenhouse gas
(GHG) emission (as carbon dioxide equivalent emission—CO2eq), land use, acidifying emission (as sulphur
dioxide equivalent emission—SO2eq), eutrophying emissions (as phosphate equivalent emissions—PO43−eq),
freshwater withdrawals, and stress-weighted water use per 1000kcal of diet, according with the metabolizable
energy of the diet and the percentage of inclusion of each ingredient in the diet, as the equation below:
To obtain these results, the diet composition was rst converted from a dry matter basis to a 1000kcal basis
using the following equation, applied to all ingrediets present in the diet:
e comparison per 1000kcal was used to put all diets on a basis of dietary intake, as a dog or cat requires
the same energy intake regardless of the diet chosen and is a reliable unit to compare dietary composition and
nutrient intake.
e data used to estimate the variables of environmental impact was based on the data from Poore and
Nemecek7 for nutrition functional units as 1000kcal. When data was provided per 100g protein or per kg of
product, it was converted to 1000kcal based on data from ABINPET35, Butolo36, TACO38, and USDA37 (TableS4).
e ingredients were classied in one of the 43 groups listed by Poore and Nemecek7, for example, all types of
beef meat were calculated as bovine meat.
Furthermore, the relationship between the dietary nutrient composition and the variables that were used to
evaluate the environmental impact was assessed.
Statistical analysis. e statistical analysis was performed using R Core Team40. Adherence to normality
was tested with the Shapiro–Wilk test, and as only the variables crude protein concentration and NFE of website
homemade diets, and SO2eq of dry diets were considered to adhere to normality, non-parametric tests were per-
formed. For the analysis of macronutrient prole and the estimated environmental impact, the Kruskal–Wallis
test was used to compare variables. When at least one median was considered dierent, multiple comparisons
between groups were performed. e comparison between energy provided by ingredients of vegetable and ani-
mal origin was performed with the Wilcoxon test, considering the variables as two dependent samples. Values
of p < 0.05 were considered signicant.
e principal component analysis (PCA) was used to evaluate the relation between the diet characteristics and
the variables of environmental impact. As the units of the variables were dierent, they were scaled considering
mean = 0 and variance = 1. e rst (PC1) and second principal components (PC2) were responsible for 68.2% of
the data variance for dogs (Fig.S3). For cats, PC1 and PC2 are responsible for 71.1% of the data variance (Fig.S4).
Data availability
e datasets generated during and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Received: 13 June 2022; Accepted: 18 October 2022
References
1. Charles, N. & Davies, C. A. My family and other animals: Pets as kin. Sociol. Res. Online 13, 1–14 (2008).
2. IBGE. Pesquisa Nacional de Saúde 2013: Acesso e Utilização dos Serviços de Saúde, Acidentes e Violências. Pesquisa de Orçamentos
Familiares 2008–2009 (IBGE, 2015).
3. Pet Secure. A Guide to Worldwide Pet Ownership. https:// www. petse cure. com. au/ pet- care/a- guide- to- world wide- pet- owner ship/
(2019).
4. American Veterinary Medical Association. AVMA Pet Ownership and Demographics Sourcebook (AVMA, 2018).
5. Swanson, K. S., Carter, R. A., Yount, T. P., Aretz, J. & Bu, P. R . Nutritional sustainability of pet foods. Adv. Nutr. 4, 141–150 (2013).
6. Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).
% NFE
=
100
−
(% crude protein
+
% crude fat
+
% crude fiber
+
% ash
+
% moisture).
Impact variable per
1000 kcal =
Amount of ingredient /1000 kcal of diet
×
Variable/1000 kcal of ingredient
1000 kcal
Amount of ingredient per
1000 kcal =
Amount of ingredient per kg of diet
×
1000
Metabolizable energy of the diet (kcal/kg)
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Vol.:(0123456789)
Scientic Reports | (2022) 12:18510 | https://doi.org/10.1038/s41598-022-22631-0
www.nature.com/scientificreports/
7. Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).
8. FAO. e state of the world’s land and water resources for food and agriculture. in Lecture Notes in Computer Science (Including
Subseries Lecture Notes in Articial Intelligence and Lecture Notes in Bioinformatics.). Vol. 10907 LNCS. (Food and Agriculture
Organization of the United Nations, 2011).
9. Allwood, J. M., Bosetti, V., Dubash, N. K., Gómez-Echeverri, L. & von Stechow, C. Glossary. in Climate Change 2014: Mitigation
of Climate Change. 1247–1279 (Cambridge University Press, 2014).
10. Ritchie, H. & Roser, M. Environmental impacts of food production. on Our World Data. https:/ / ourwo rldin data. org/ envir onmen
tal- impac ts- of- food (2020).
11. Su, B., Martens, P. & Enders-Slegers, M.-J. A neglected predictor of environmental damage: e ecological paw print and carbon
emissions of food consumption by companion dogs and cats in China. J. Clean. Prod. 194, 1–11 (2018).
12. Su, B. & Martens, P. Environmental impacts of food consumption by companion dogs and cats in Japan. Ecol. Ind. 93, 1043–1049
(2018).
13. Okin, G. S. Environmental impacts of food consumption by dogs and cats. PLoS ONE 12, 1–14 (2017).
14. Alexander, P., Berri, A., Moran, D., Reay, D. & Rounsevell, M. D. A. e global environmental paw print of pet food. Glob. Environ.
Chang. 65, 102153 (2020).
15. FEDIAF. Nutritional Guidelines for Complete and Complementary Pet Food for Cats and Dogs. (Fédération Européenne de l’Industrie
des Aliments pour Animaux Familiers, 2020).
16. Climate Watch. Climate Watch-Brazil. Greenhouse Gas Emissions and Emissions Targets. https:// www. clima t ewat chdata. org/ count
ries/ BRA? calcu lation= PER_ CAPITA (2020).
17. Michel, K. E. Unconventional diets for dogs and cats. Vet. Clin. N. Am. Small Anim. Pract. 36, 1269–1281 (2006).
18. Connolly, K. M., Heinze, C. R. & Freeman, L. M. Feeding practices of dog breeders in the United States and Canada. J. Am. Vet.
Med. Assoc. 245, 669–676 (2014).
19. Laamme, D. P. et al. Pet feeding practices of dog and cat owners in the United States and Australia. J. Am. Vet. Med. Assoc. 232,
687–694 (2008).
20. Dodd, S. et al. An observational study of pet feeding practices and how these have changed between 2008 and 2018. Vet. Rec. 186,
643 (2020).
21. Stevenson, A. E., Hynds, W. K. & Markwell, P. J. Eect of dietary moisture and sodium content on urine composition and calcium
oxalate relative supersaturation in healthy miniature schnauzers and labrador retrievers. Res. Vet. Sci. 74, 145–151 (2003).
22. Buckley, C. M., Hawthorne, A., Colyer, A. & Stevenson, A. E. Eect of dietary water intake on urinary output, specic gravity and
relative supersaturation for calcium oxalate and struvite in the cat. Br. J. Nutr. 106(Suppl), S128-130 (2011).
23. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensication of agriculture. Proc. Natl.
Acad. Sci. U.S.A. 108, 20260–20264 (2011).
24. NRC. Nutrient Requirements of Dogs and Cats (National Academy Press, 2006).
25. Zafalon, R. V. A. et al. Nutritional inadequacies in commercial vegan foods for dogs and cats. PLoS ONE 15, 1–17 (2020).
26. Macleod, M. et al. Greenhouse Gas Emissions from Pig and Chicken Supply Chains—A Global Life Cycle Assessment. Food and
Agriculture Organization of the United Nations (Food and Agriculture Organization of the United Nations, 2013).
27. Gerber, P. J. et al. Tackling Climate Change rough Livestock—A Global Assessment of Emissions and Mitigation Opportunities. Vol.
14 (Food and Agriculture Organization of the United Nations, 2013).
28. Oliveira, P. P. A. et al. Greenhouse gas balance and carbon footprint of pasture-based beef cattle production systems in the tropical
region (Atlantic Forest biome). Animal 14, s427–s437 (2020).
29. Mazzetto, A. M., Feigl, B. J., Schils, R. L. M., Cerri, C. E. P. & Cerri, C. C. Improved pasture and herd management to reduce
greenhouse gas emissions from a Brazilian beef production system. Livest. Sci. 175, 101–112 (2015).
30. ABRA. Anuário ABRA: Setor de Reciclagem Animal. (2019).
31. ABRA. II Diagnóstico da Indústria Brasileira de Reciclagem Animal. (2016).
32. Leenstra, F., Vellinga, T. & Bessei, W. Environmental footprint of meat consumption of cats and dogs. Lohmann Inf. 52, 32–39
(2018).
33. Oonincx, D. G. A. B. & de Boer, I. J. M. Environmental impact of the production of mealworms as a protein source for humans—A
life cycle assessment. PLoS ONE 7, 1–5 (2012).
34. Optimal Informática Ltd. Optimal Formula 2000. (2019).
35. ABINPET. Manual Pet Food Brasil. (Centrograca, 2017).
36. Butolo, J. E. Qualidade de Ingredientes na Alimentação Animal (Mundo Agro Editora, 2010).
37. USDA. Food Data Central. Food Data Central https:// fdc. nal. usda. gov/ (2020).
38. TACO. Tabela Brasileira de Composição de Alimentos. (NEPA-UNICAMP, 2011).
39. Atwater, W. O. Principles of nutrition and nutritive value of food. in Farmer’s Bulletin. Vol. 142 (United States Department of
Agriculture, 1902).
40. R Core Team. R: A Language and Environment for Statistical Computing. https:// www.r- proje ct. org/ (2020).
Acknowledgements
We would like to thank Grandfood Industry and Commerce (PremieR pet) for funding our Veterinary Nutrology
Service at the School of Veterinary Medicine and Animal Science of University of Sao Paulo, Brazil.
Author contributions
Conceptualization: V.P. Methodology: V.P. and F.A.T. Investigation: V.P. and F.A.T. Formal analysis, Data curation
and Visualization: V.P., F.A.T. and M.R.Q. Supervision: V.P. and M.A.B. Writing—original dra: V.P. and F.A.T.
Writing—review & editing: V.P., F.A.T. and M.A.B
Funding
V.P. was supported by a Coordination of Superior Level Sta Improvement (CAPES-Brazil) doctorate scholarship.
Competing interests
Dr. Brunetto’s Pet Nutrology Research Center has been funded by Grandfood industry and Commerce (PremieR
pet), and Dr. Teixeira and MSc Pedrinelli are both part of the research group. Dr Queiroz declares no potential
conict of interest.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 022- 22631-0.
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