Income Equality Than It Is to Welfare Is Related More to ......NONHUMAN ANIMAL WELFARE AND INCOME...
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Improved Nonhuman AnimalWelfare Is Related More toIncome Equality Than It Is toIncomeMichael C. Morris aa New Zealand Centre for Human Animal Studies,University of Canterbury , Christchurch , NewZealandPublished online: 24 Jun 2013.
To cite this article: Michael C. Morris (2013) Improved Nonhuman Animal WelfareIs Related More to Income Equality Than It Is to Income, Journal of Applied AnimalWelfare Science, 16:3, 272-293, DOI: 10.1080/10888705.2013.768921
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JOURNAL OF APPLIED ANIMAL WELFARE SCIENCE, 16:272–293, 2013
Copyright © Taylor & Francis Group, LLC
ISSN: 1088-8705 print/1532-7604 online
DOI: 10.1080/10888705.2013.768921
Improved Nonhuman Animal Welfare IsRelated More to Income Equality Than
It Is to Income
Michael C. Morris
New Zealand Centre for Human Animal Studies,
University of Canterbury, Christchurch, New Zealand
The link between nonhuman animal welfare, income, and income inequality (Gini
coefficient) was tested using consumption of animal products, laws protecting
animals on the farm from the worst abuses, and animals used in experimentation as
indicators. Experimentation on all animals and on rodents significantly increased
in high-income European countries, although there was some evidence that the
increase in experimentation on cats and dogs started to flatten out for the highest
income countries. Consumption of all flesh products in high-income countries
declined in more equal societies. More equal high-income countries also had
stricter regulations protecting animals, although the same correlation was not seen
between U.S. states. In New Zealand, there was some evidence that testing on
cats and dogs declined during years when equality was improving. The results
provide little evidence for a Kuznets effect of income on animal welfare, with the
possible exception of companion animal treatment. They do, however, suggest that
greater equality can be a predictor for better treatment of animals. Previous research
has strongly suggested that social conditions for humans improve with greater
equality. The same may be true for nonhuman animals. Alternatively, conditions
conducive to improving human income equality may also lead to better animal
welfare outcomes.
Keywords: animal welfare, Kuznets curve, inequality, Europe, United States, New
Zealand
Correspondence should be sent to Michael C. Morris, New Zealand Centre for Human Animal
Studies, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. Email:
272
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 273
The environmental literature discusses the Environmental Kuznets Curve (EKC),
which is the hypothesis that as the per capita income of countries improves, their
effect on the environment initially increases as polluting industries grow, but thenit starts to decline again after a threshold of income is reached (Carson, 2010).
When comparing only the highest income countries (or subnational entities)
the EKC predicts that levels of environmental protection would be positively
correlated with income.
Reasons proposed for higher income countries or states reducing their en-vironmental impact include improvements in technology (Carson, 2010) and
a shift in the attitudes of wealthier consumers who can afford the luxury of
altruism and a higher level desire for aesthetics and the environment once their
basic needs have been met (Frank, 2008; Lantz & Martinez-Espineira, 2008).
So far, actual evidence for an EKC has been mixed. When comparing dis-
charge rates of locally produced air and water pollutants, an EKC was detected insome cases (Carson, 2010) but not in others (Akbostanksi, Turut-Asik, & Tunc,
2009; Murad & Mazumder, 2009). When considering environmental “goods” and
not “harms,” Lantz and Martinez-Espineira (2008) found a positive correlation
between average per capita state income and the increase in population of
protected bird species in Canadian states. An analysis of seven environmental“harms,” comprising damage to the atmosphere, terrestrial, marine, and fresh-
water ecosystems, found no evidence of an EKC. Relative resource depletion
decreased linearly with increase in per capita income, and absolute resource
depletion showed no correlation (Bradshaw, Gima, & Sodhi, 2010).
Income effects may reflect the different type of political action requiredto improve “goods” or redress “harms.” The former requires state investment
in labor, land, or infrastructure when considering putting more land aside for
reserves, for example, and it would therefore be a prerogative of wealthier states.
The latter, however, requires states to curtail the activities of polluters, who may
have immense wealth and political power. Success in this venture would be
dependent not on the income of the state but on power disparities and politicalwill.
Bird protection has a positive effect on nonhuman animal welfare as well as on
conservation, as do some other environmental effects such as habitat destruction
and pollution of wildlife habitat, so it is possible that an Animal Welfare Kuznets
Curve (AWKC) may also exist. This hypothesis was proposed by Frank (2008),who pointed out that the same conditions of increasing technology and higher
order desires would apply to both animal welfare and environmental protection.
However, just as with the EKC, the evidence for an AWKC is mixed. Frank
(2008) found that some positive attitudes toward animal welfare were correlated
with income in Europe and that high-income U.S. states were the ones withfelony-level animal cruelty statutes and more humane euthanasia methods in
shelters. However, meat consumption, arguably the biggest contributor to animal
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274 MORRIS
suffering in both numbers and intensity of suffering (Eisnitz, 1997; Morris, 2011;
Webster, 1997), actually increased in the United States during years when the
country had greater average income.Some welfare indicators such as number of animals used in experiments
declined over time, and Frank (2008) concluded that this indicated an improve-
ment in welfare with increased economic growth. However, there is evidence
that developments in societal knowledge and attitudes have led to continuous
improvements in both animal and human welfare over the last 4 centuries, andparticularly over the last 40 years or so, with the increase in the number and
effectiveness of environmental and animal rights pressure groups (Pinker, 2011;
Thomas, 1983). A reduction in the number of animals used and intensity of
suffering with time, regardless of income changes, is therefore likely, and this
will confound any income effect where historical data is used.
Another criticism of the EKC is that is fails to take income inequality intoaccount (Carson, 2010). It is possible that the way income is distributed may
be more important than absolute average income. Income inequality has been
found to be correlated with just about every social ill in the social scientists’
sights, including crime, incarceration rates, teen pregnancy, mental illness, and
obesity (Wilkinson & Pickett, 2010). More recent research suggests a similarlink between income inequality and environmental indicators, including meat
consumption (Wilkinson, Pickett, & De Vogli, 2010), which is also an animal
welfare indicator. Correlations between environmental protection and animal
welfare with income may be indirect, and it is really greater equality and
empowerment of individuals that are contributing to better welfare.Reasons proposed for the correlation of self-destructive or other-destructive
behavior with inequality include a lack of trust among unequal communities and
feelings of isolation, alienation, envy, and competition that these communities
encourage (Wilkinson & Pickett, 2010). In other words, there is a desire for
self-gratification or to feel better through domination of others. The same urges
could lead to worse animal welfare outcomes at least as far as gratuitous crueltyis concerned, but they may also lead to less caring attitudes in general and
to a population quite willing to maintain the level of “affected ignorance”
(Williams, 2008) required to continue with institutional inhumane practices.
At the individual level, those who are not struggling to survive may have
more time to devote to thinking about other species or to volunteer for animalcauses. Alternatively, factors that lead to income disparities, such as the power of
corporations keeping down wages and pushing up chief executives’ salaries, may
also affect animal welfare through increases in agribusiness and pharmaceutical
activities.
This study attempts to test whether a link between animal welfare and in-equality is more likely than a Kuznets curve by testing different indicators for
animal welfare and correlating these with indicators for income and income
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 275
inequality. Because other factors such as improvements with time may have an
impact on animal welfare indicators, and because in some cases income may
be correlated with inequality as predicted by the original Kuznets (1955) curve,partial correlations are used where appropriate.
INDICATORS FOR ANIMAL WELFARE
Indicators chosen were consumption of animal products, laws protecting animals,
and animals used in experimentation. The largest contribution to animal suffering
is the factory farming of animals for meat, eggs, and other food, which requiresthe greatest number of animals as well as arguably the worst suffering (Morris,
2011; Webster, 1997). For this reason, regulations prohibiting these extremes of
factory farming are also included as an indicator.
Frank (2008) suggested that overall animal welfare impact can be defined in
terms of the effect on each animal and the total number of animals suffering.A weighting is used for each animal to recognize that species differ in level of
sentience and future awareness, and this has an impact on suffering experienced
(Varner, 1999).
Animal welfare impact is given by the following equation:
Animal Welfare Impact D
X
i
X
t
Œ.Uit1 � Uit0/ � Wi�
where the utility (U) for each animal affected (i) over time (t) is dependent on the
difference between the utility experienced when particular activities or policies
continue over time (Uit1) compared with the utility experienced if such activities
or policies do not take place (Uit0). The term Wi is the weighting factor, which
is applied to each animal affected by an activity or policy.
The term Uit1 � Uit0 is negative if an activity is worse from an animal welfareperspective than nonexistence, and it is positive if it is better. It is a standard
argument used by those opposing veganism, for example, animals would actually
be worse off if we did not eat their flesh or other products because they would
not exist.
However, when considering all animals involved in farming for food, it is verydifficult to argue that the utility of any animals would be better when compared
with eliminating farming. First of all, most farming is not benign, and it should
be taken as a basic axiom that the inhumane treatment of factory farmed animals,
who make up the majority of those eaten for meat, is far less desirable from the
animals’ point of view than nonexistence (Morris, 2011; Webster, 1997). Eventhe most benign farming practices involve an opportunity cost of using land that
cannot be set aside for wildlife. Increasing the land in cultivation for animal
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276 MORRIS
production also increases the number of animals in the wild killed (Matheny,
2003). For these reasons, I am assuming that animal farming always leads to
negative utility.It is also likely that the utility function would be negative for animal experi-
ments, even those that do not involve extreme suffering. Experimental animals
for research, teaching, and testing come from a variety of sources. Some are
animals on the farm, who are killed at the end of the experiments or returned
to pasture if the manipulation is minor or is part of normal farming practices.These animals would suffer not just from the normal effects of farming but also
from the manipulation, even if it is minor (Morris & Weaver, 2003).
The only case where experimentation could lead to a positive utility may be
when animals are specially bred for experiments, but even this is unlikely given
that these animals are usually rodents, and they are generally reserved for the
most severe of suffering, which they experience in addition to the stress fromthe confinement itself (e.g., Callard, Bursten, & Price, 2010).
Frank (2008) did not future discount the animal welfare function. Although
animal rights advocates may consider that the rights of presently existing animals
are more important than hypothetical ones (Regan, 2004), a lack of future
discounting is more appropriate for a more utilitarian animal welfare stance(Singer, 1991), where the welfare of future animals is no less important than
present ones.
In most places, animals in research, testing, and teaching make up the bulk
of all animals killed who are not eaten for food. In some countries like New
Zealand, extermination of pest animals would rank higher in numbers thananimals killed or painfully manipulated in laboratories (Parliamentary Commis-
sioner for the Environment [PCE], 2011). However, because the preservation
of native animals may depend on their demise, it could possibly be argued
that their extermination could benefit animals overall from a utilitarian animal
welfare point of view (i.e., Ut � Ut0 > 0 for wildlife), depending on how humane
the control method is (PCE, 2011). For this reason, animal experimentation waschosen over vertebrate pest control as an indicator for the second worst instance
of an activity leading to negative animal welfare utility.
INCOME AND INEQUALITY INDICATORS
Kuznets curves were tested using only high-income countries and U.S. states
unless otherwise stated because it is only the right-hand arm of the curve
(where the negative effect being tested declines with income) that is of interest.Wilkinson and Pickett (2010) also only tested the link between inequality and
social ills among the highest income countries (per capita incomes of $20,000
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 277
or more), as the social effects of inequality stand out more among high-income
countries.
Inequality for nation-states was measured using the income Gini coeffi-cient (2000–2010) from the United Nations Human Development Index (2010;
hdr.undp.org/en/reports). For U.S. states, the Gini coefficient from the American
Community Survey of the U.S. census was used (2009 data). The income
indicator chosen for nation-states was the Gross National Income per person,
adjusted for purchasing power parity (GNI PPP) in international dollars from theWorld Bank data, because this would give a measure of the average real spending
power of residents. For U.S. states, the average per capita income (in 2011
inflation-adjusted U.S. dollars) from the American Community Survey (2007–
2011; http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml) was used.
INCOME, INEQUALITY, AND ANIMAL
PRODUCT CONSUMPTION
The total mass of animal flesh and animal products consumed, and the number ofcalories and proportion of calories obtained from animal or vegetable products,
were taken for 2007 (the latest year available) from the Food and Agriculture
Organization (FAO) FAOSTAT database online. This was correlated against 2007
figures for GNI PPP and the Gini coefficient for the 50 highest income countries
in 2007, excluding those with a population under 3 million, to exclude taxhavens (Wilkinson & Pickett, 2010). No FAO data were available for Singapore
or Hong Kong, so these countries were excluded. The correlation coefficient
between income and Gini approached significance (r D �0.3, p < .1), indicating
a possible Kuznets (1955) effect as equality improved with income in the
higher income countries. Partial correlations were therefore used with income
and inequality as dependent variables and animal product consumption as theindependent variable.
There was no significant partial correlation between income and meat con-
sumption or calories derived from animal products (Table 1, Figure 1). Total
meat, bovine meat, and poultry meat consumed all increased significantly as the
Gini increased (Table 1, Figure 2); total calorific consumption also increased.There was no correlation with pig meat, sheep and goat meat, seafood, or egg
consumption and the Gini coefficient (Table 1).
The low meat consumption of Norway may suggest that meat consumption
in very high income countries is declining, suggesting a Kuznets effect. How-
ever, when results were reanalyzed only for the top 12 countries by income, acorrelation was still not found with income, although the correlations with Gini
were still present.
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278 MORRIS
TABLE 1
Partial Correlations Between Indices of Animal Product Consumption and Income and
Income Inequality (Gini Coefficient) for the Wealthiest Countries in 2007
Correlation
With Income
Correlation
With Inequality
(Gini Coefficient)
Index
Mean
Consumption
per Person
Correlation
Coefficient
Significance
Level
Correlation
Coefficient
Significance
Level
Total meat
(kg per year)
88.42 (4.15) 0.11 ns 0.56 p < .01
Total bovine meat
(kg per year)
22.80 (1.80) 0.38 ns 0.58 p < .01
Total pig meat
(kg per year)
34.70 (2.96) �0.09 ns �0.24 ns
Total poultry meat
(kg per year)
24.87 (2.83) 0.11 ns 0.65 p < .01
Total mutton and goat
meat (kg per year)
4.03 (1.19) 0.19 ns 0.21 ns
Total eggs
(kg per year)
11.93 (0.75) 0.09 ns �0.35 ns
Total fish and seafood
(kg per year)
29.23 (2.83) �0.25 ns �0.30 ns
Total calories
(per day)
3429 (52.16) 0.34 ns 0.54 p < .01
Total animal calories 1007 (40.00) 0.35 ns 0.02 ns
Total vegetable
calories (per day)
2421 (50.60) 0.05 ns 0.51 p < .02
Proportion of
vegetable calories
0.71 (0.01) �0.28 ns 0.16 ns
The results confirm those already found by Doring (2010) that less meatis consumed in more equal societies. Animal welfare is not the only reason
for cutting back on meat consumption; awareness of health effects and en-
vironmental consequences could also have a bearing. However, the result is
still an improvement in animal welfare regardless of reason. There is also
evidence that animal welfare may play some part in choices to cut back onmeat. Chicken meat contains less saturated fat than red meat, so it is usually
considered healthier. Chicken production also has a lower carbon footprint and
causes less environmental damage than cattle farming (D’Silva & Webster, 2010;
Eshel & Martin, 2006), so it would be expected that those only concerned with
health or the environment would switch from red meat to chicken, a trend thathas been found in the United States (Frank, 2008). However, consumption of
chicken meat was also significantly lower in more equal countries (Figure 2),
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 279
FIGURE 1 Total mass of meat consumed per person in 2007, with Gross National Income
(Purchasing Power Parity) (GNI PPP), for the highest income countries with a population
over 3 million. Outliers are shown.
which is good news for animal welfare given the number of chickens requiredand the suffering inherent in modern broiler production (Morris, 2009). There
was no significant increase in consumption of eggs or seafood in more equal
countries to compensate for less red meat or poultry being consumed (Table 1).
LAWS ON SPECIFIC ANIMAL PRACTICES
National or Federal-Level Laws
Most developed countries have a law passed by the legislature at the national
or federal level that condemns animal cruelty. However, unless the laws are
accompanied by regulations outlining requirements for specific animal practices,
the laws have little effect on animal welfare. The Hong Kong Prevention of
Cruelty to Animals Ordinance (1997), for example, has the purpose “to prohibitand punish cruelty to animals.” In Japan the Industry Standard for the Care and
Keeping of Animals (Prime Minister’s Notice No. 22, 1987) includes a clause
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280 MORRIS
FIGURE 2 Total mass of meat (diamonds), and mass of chicken meat (triangles) and
bovine meat (squares) consumed per person in 2007 by Gini for the 21 highest income
countries with a population over 3 million. Lines of best fit are shown for significant
correlations.
stipulating suitable husbandry conditions (Clause 3). In spite of these regulations,
there is no control over intensive practices such as battery hen cages or sow stalls
in either country.Laws prohibiting or restricting specific practices may not be promulgated for
animal welfare concerns but in order to placate the public or overseas consumers
(Beatson, 2008; Francione, 1996). However, the fact that members of the public
have sufficient awareness to require placation and to enforce their desires through
political or court action suggests that the presence of more specific regulations
is a useful indicator for improvements in animal welfare in the present or nearfuture.
It has been suggested by opponents of government regulation that restrictions
on animal production for welfare reasons may be counterproductive because
they raise the prices of the domestic products, leading to cheaper imports
from countries with fewer welfare restrictions. However, societies in countrieswith regulations prohibiting the worst welfare practices have demonstrated they
consider animal welfare ethically important and furthermore have sufficient
political will to translate ethics into policy. It is likely that the same ethical
standard and political will can be used to restrict imports of products that do not
reach the same standard of welfare as the domestic product, which occurred, forexample, when the European Union banned products containing cat or dog fur
or Canadian products derived from seals (Stevenson, 2009).
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 281
A table of regulations prohibiting or phasing out the practices most widely
targeted by animal advocacy groups such as People for the Ethical Treatment of
Animals (PETA), The Humane Society of the United States, the various Societiesfor the Prevention of Cruelty to Animals, Save Animals From Exploitation, and
Compassion in World Farming was compiled. The highest income countries
in 2009 (the latest year for which economic data is available) were scored in
a dummy variable for the number of regulations protecting animal welfare in
place. For each of the following activities, one point was scored if there is aregulation in place phasing it out, and one point was scored if the ban was in
force when the data were analyzed (August 2011).
1. A ban on farrowing crates.
2. A ban on sow crates for the entire pregnancy.
3. A ban on battery cages.
4. A ban on the “colony” or “enriched” cages for hens.
One point was also scored for each of the following two regulations that were
already in force. This included countries like New Zealand where the codes
of welfare would effectively prohibit a practice even if it is not specificallymentioned in the regulation.
1. A current ban on veal crates.
2. A current ban on foie gras production.
There was not a discernible correlation between income and the Gini coefficient
for the countries analyzed (r D 0.02), so partial correlation or blocking was not
performed.
Protective regulations declined significantly with the Gini coefficient (r D
�0.50, p < .05) in spite of outliers from two non-European countries (Japanand Canada) with lower levels of animal protection than predicted from their low
Gini coefficients. A correlation with income was not found (r D 0.03). When
only the 12 highest income countries were analyzed, there was still a significant
decline in protective regulations with the Gini coefficient but no correlation with
income. This indicates that overall there was no evidence of a Kuznets curve,but there was evidence of an inequality effect (Figure 3).
When each regulation was tested separately using a t test, the countries that
had enacted bans on battery cages (European Union countries plus Norway and
Switzerland) had a significant lower Gini coefficient than the other countries
(Gini averages 31.03 and 36.85, respectively, p < .05). There was a similareffect for those countries with a ban in force on battery cages (Norway, Swe-
den, Finland, and Switzerland) compared with the rest (Gini 27.85 and 34.15,
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FIGURE 3 Number of bans on factory farming practices for high-income countries, with
Gini coefficient (top) and income (bottom). Outliers are shown. Lines of best fit are shown
for significant correlations. GNI PPP D Gross National Income (Purchasing Power Parity).
(Color figure available online.)
282
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 283
TABLE 2
Statistical Tests Comparing Legal Protection of Animals in U.S. States
and Income and Gini Coefficient
Variable
States With Regulations
Limiting Confinement
of Food Animals All Other States Significance
Average income (with SEM) $27,315 (779) $27,787 (739) ns
Average Gini (with SEM) 45.2 (0.46) 44.95 (0.38) ns
Note. SEM D Standard Error of the Mean.
respectively, p < .05). There were no significant differences in Gini or income
between countries with bans on any of the other practices.
State-Level Laws in the United States
Seven U.S. states have laws banning or phasing out intensive farming practices:
Arizona, California, Colorado, Maine, Florida, Michigan, and Oregon. There wasnot a significant difference between the per capita income or Gini coefficient
of states with or without restrictions (Table 2). Centner (2010) has argued that
laws restricting farming practices might have been passed because the practices
being restricted do not make major contributions to the economies of the states,
and this factor would appear to be a stronger influence than social or economicindicators generally.
A more comprehensive analysis of animal protection laws has been compiled
by the Animal Legal Defense Fund (Otto, 2011). This organization ranks all U.S.
states against a list of criteria that includes not just legal protection for animals
from inhumane practices but also considerations such as penalties, enforcement,
funding, legal protection, and mental health evaluations and counseling foroffenders.
However, even when this more comprehensive ranking was correlated with in-
come and Gini coefficients, there still were no significant correlations (Table 3).
It appears that the better protections afforded to animals in more equal countries
are not repeated at the subnational level within the United States.
TABLE 3
Correlations Between U.S. Animal Protection Laws Rankings for All U.S. States
Variable Correlation Coefficient Significance
Correlation with income �0.07 ns
Correlation with Gini coefficient �0.09 ns
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284 MORRIS
ANIMAL EXPERIMENTATION AND TESTING
Finding reliable data for the number of animals used for research, education,and testing is fraught with difficulty given that states and countries differ in their
reporting requirements. The fact that rats, mice, birds, reptiles, and amphibians
are not even protected by the U.S. Federal Animal Welfare Act (1966) in spite
of making up the largest number of animals tested is a bone of contention
among U.S.-based animal advocacy groups. Criticism of this regulatory gapcan be found on the websites of PETA, the National Anti-Vivisection Society,
the Animal Legal Defense Fund, and Physicians Committee for Responsible
Medicine.
However, two direct comparisons can be made based on available data.
European Animal Use
Directive 86/609/EEC requires countries of the European Union to submit stan-
dardized reporting for the number of animals manipulated, broken down by
species, with the latest data available for 2008 (European Commission, 2010).
However, it is important to note that the figures give no indication of theproportions of animals used who were subsequently killed or the degree of
suffering the animals were subjected to.
Animal use data in 2008 for 20 European countries with a population over
3 million were analyzed. The correlation between Gini coefficient and income
was not significant, but it was reasonably high for all countries and for the highestincome countries (r D �0.21 and �0.18, respectively). Partial correlations were
therefore calculated together for all countries and then separately for the 15
countries with a 2008 GNI PPP of more than $20,000. These were compared
for the independent variables of all animals, all rodents, all primates, and all
cats and dogs used per capita.There was a significant partial correlation with income for rodents and all
animals, for all 20 countries, and for the 15 high-income countries. Rodents
made up the majority of animals used. The number of cats and dogs used
increased significantly with income for all countries but not when only the
high-income countries were counted, which suggests a Kuznets effect with the
increase flattening for the highest income countries (Table 4, Figure 4).
New Zealand Animal Use
In New Zealand, there have been regulations in place since 1987 stipulating thatinstitutions must keep adequate records of animals killed for research, testing,
or teaching and that the executive government make these available. From 1998
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TABLE 4
Partial Correlations Between Indices of Animal Experimentation in Europe and
Income and Income Inequality (Gini Coefficient) in 2009
All Countries High-Income Countries
Type of Animal Income Gini Income Gini
All animals 0.61** �0.33 0.60** �0.29
Rodents 0.60** �0.17 0.65* �0.09
Cats and dogs 0.44* �0.19 0.40 �0.15
Primates 0.37 0.25 0.24 0.27
Note. Correlations are calculated separately for all countries and for those with incomes over
$20,000.
*p < .05. **p < .01.
onward, it has also been a requirement that the level of suffering be recorded
according to criteria from the Ministry of Agriculture. Suffering is defined as
“little or none,” “medium,” “severe,” or “very severe.” The term “suffering” was
changed to the more euphemistic “impact” in 2008, but the types of experimentscovered are essentially the same. See New Zealand Animal Welfare Act 1999
and associated regulations.
Using historical data does, however, mean that the results can be influenced
by improvements in welfare with time. In keeping with other Organisation for
Economic Co-operation and Development countries with a policy of continuouseconomic growth, the trend in New Zealand was for an increase in per capita
income each year from 1987 to 2010 (r D 0.99, p < 10�5).
Gini coefficients were calculated directly from the Statistics New Zealand
Household Economic Survey every 2 to 3 years and were extrapolated for other
years. The Gini coefficients have moved steadily upward in New Zealand since
1988 (r D 0.83, p < .001), although this trend was reversed slightly from 2000to 2007.
The number of cats and dogs killed per person and the total number of animals
killed per person declined significantly over time. There was no significant time
effect for the number of rodents killed or for “suffering” or “severe” suffering
experiments (Table 4, Figure 5).The decline in animal use may be related to a deliberate policy of Replace,
Reduce, Refine as promoted by government; the increased militancy of pressure
groups and the effects they are having on experimenters (Festing, 2005); or a
general decline in invasive treatment of human and nonhuman animals alike
(Pinker, 2011). In the case of rodents, reductions may be balanced by a counter-vailing factor, an increase in the number of genetically modified animals used
in more recent years (Collins, 2004).
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FIGURE 4 Number of rodents (squares) and all animals (diamonds) used per thousand
people for the 20 European Commission countries, with Gross National Income (Purchasing
Power Parity) (GNI PPP) (top) and Gini (middle). The bottom panel shows the number of
cats and dogs used per hundred thousand people with GNI PPP. Lines of best fit are shown
for significant correlations. Outliers are shown.
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 287
FIGURE 5 Total number of animals killed (top), number of cats and dogs killed (middle),
and number of rodents killed (bottom) proportional to population, for the reporting years
1988 to 2010, in New Zealand. Lines of best fit are shown for significant correlations.
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TABLE 5
Correlations Between Animals Killed and Animals Suffering in Experiments and Year,
Changes in Gini and Income, and Income Inequality for New Zealand
Type of Animal/Manipulation
(per Person per Year)
All
Animals
Killed
Cats and
Dogs Killed
Rodents
Killed
“Severe” and
“Very Severe”
Suffering
Correlation with year �0.42* �0.73** �0.22 �0.15
Correlation with change in Gini 0.32 0.53* 0.08 0.21
Correlation with change in income 0.08 �0.32 0.08 0.00
Correlations with change in Gini
between directly measured Gini years
0.30 0.58 0.03 0.36
Correlations with changes in income
between directly measured Gini years
0.36 0.53 0.31 0.39
Note. Data for animals killed are from 1988 to 2010, and for suffering the data are from 1998 to
2010.
*p < .05. **p < .01.
Because income and inequality are so closely correlated with time, it is
not accurate to use partial correlation or regression to distinguish the influencethat these economic indicators may have (Newbold, Carlson, & Thorne, 2010).
For this reason, animal use was correlated with changes in income and Gini
coefficient from the previous year, which showed no correlation with year and
no correlation with each other.
There was a significant positive correlation between the number of cats and
dogs killed with changes in the Gini coefficient, indicating that more of theseanimals were killed in years where inequality was improving (Table 5, Figure 6).
Because animal experimentation may be planned over several years and not just
one, the number of animal experiments was grouped between years where the
Gini was measured directly. The correlation between cats and dogs killed and the
change in the Gini coefficient was not significant for a two-tailed test, althoughit was still high (p < .1; Table 5).
No other variables showed any significant correlation with change in the Gini
coefficient. There was no significant correlation between change in income and
any of the variables tested.
SUMMARY OF FINDINGS
Animal Welfare and Income
The number of live animals used in state veterinary schools in the United
States was significantly lower in schools with higher incomes. It is possible
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 289
FIGURE 6 Cats and dogs killed in New Zealand per million people for the years 1988 to
2010, with changes in the Gini coefficient during the previous year. Line of best fit is shown
for a significant correlation.
that the number of animals killed in shelters also declines with increasing
income (Frank, 2008). Balancing these trends, however, is the tendency for
animal testing to actually increase in high-income countries (Table 4, Figure 4).
At the individual level, meat consumption increases with income (Gossard &York, 2003), although at the country level there was no significant correlation
between animal product consumption and per capita income (Table 1, Figure 1).
Testing of cats and dogs in Europe showed no increase with income when
only high-income countries were tested (Table 4, Figure 4), indicating that if
an AWKC exists, high-income countries may be on the cusp, and if incomeincreases further, this testing may decline.
As is the case with the EKC, animal welfare “goods” such as improvements in
animal shelters and veterinary education tend to improve with income, whereas
“harms” tend to get worse or have no change. This could again be related to
the differences in the roles of the states providing more money for sheltersor alternatives to surgery in veterinary schools on the one hand, while having
tougher regulations on the meat or pharmaceutical industry on the other. All
welfare improvements that suggest an AWKC are also concerned with cats and
dogs, who enjoy a special status in many cultures.
Animal Welfare and Equality
The factor that would have the greatest influence on animal welfare on a worldscale is the consumption of meat and animal products generally. This is not only
because of the direct effects of intensive farming and killing but also because
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of the habitat destruction and global warming effects of animal agriculture, all
of which affect wildlife in different ways (D’Silva & Webster, 2010; Eshel &
Martin, 2006; Matheny, 2003).When examining meat consumption there is clear evidence that more equal
countries consume less meat overall and that this is at least partially accounted
for by animal welfare concerns (Table 1, Figure 2). More equal countries also
have stricter regulations preventing intensive farming (Figure 3).
In New Zealand, there is some evidence that testing on cats and dogs declinedin years where equality was improving (Figure 6), although no such trends were
found in Europe (Figure 4).
CONCLUSION
Economic policies focused simply on increasing income alone would appear to
lead to increased animal product consumption and animal testing and therefore
have a negative effect on animal welfare, with the possible exception of cats
and dogs. However, there is evidence that increasing equality may improve
animal welfare. Increased equality also improves human welfare and althoughthe reasons for this are not certain, one hypothesis is that it may relate to
feelings of powerlessness and lack of trust that those in less equal societies
feel (Wilkinson & Pickett, 2010). It is quite possible that this would lead to
indifference or even hostility toward those even lower on the social scale and a
desire to dominate them at the individual or societal level (Midgley, 1983).A correlation between abuse of humans and animal abuse has been well
established (Linzey, 2009) and is taken seriously by law enforcement agencies
such as the Federal Bureau of Investigation, who treat abuse of companion ani-
mals as predictors for committing crimes against humans (Brantley, Lockwood,
& Church, 2009).
Although no definitive longitudinal studies conclusively showing a causalrelationship have been conducted, there is some evidence that those who abuse
animals are desensitized to violence generally and may go on to commit violent
acts against humans. Thompson and Gullone (2006) reported that youths who
observe parents, friends, or relatives abuse animals are more likely to become
animal abusers themselves, suggesting lack of empathy is learned from rolemodels. This is further supported by studies showing how teaching empathy
toward animals leads to improvements in empathy toward humans and animals
(Beetz, 2009).
It is quite plausible therefore that the same feelings of powerlessness pos-
tulated to lead to antisocial behavior toward humans may also be linked tononhuman animal abuse. It would be more likely that this link would apply only
to gratuitous and direct violence, such as hunting and companion animal abuse,
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NONHUMAN ANIMAL WELFARE AND INCOME EQUALITY 291
which have been linked to abuse of humans and other criminal activities (Linzey,
2009). However, the decline in animal product consumption (Figure 2), tougher
laws on factory farming (Figure 3), and at least some animal testing (Figure 6)during conditions of greater equality suggest that this causal relationship also
holds true for legal and ritualized animal abuse occurring in the laboratory and
the kitchen, where there is greater emotional distance between the victims of
abuse and those responsible for, or benefiting from, the abuse.
Inequality is not the only factor that influences treatment of animals. Thereare a myriad of cultural and historical factors that need to be taken into account.
The low meat consumption found in Japan (Figure 1) may have come about, for
example, because of the combination of rugged territory and rich alluvial plains
that make it both unsuitable for cattle farming and ideal for alternative food
sources such as rice and beans (Thornhill, 2000). The food culture of Japan is
also believed to have been influenced by the Buddhist ideal of respect for life,and this is reflected in present-day food choices (Kakimoto, 2000). Historically
the Buddhist rulers of Japan frowned upon the practice of killing domesticated
livestock, considering it a betrayal of trust. The practice of hunting nonprimates
in the wild did not meet with the same opposition (Thornhill, 2000), which may
account for the reasons Japan still allows whale and dolphin hunting even whileeating very little meat. Paradoxically, the low level of protection afforded animals
in confinement may be a manifestation of the same process. The tradition of
animal farming for food in Japan has not been going on long enough to promote
awareness among regulators or the general public or to generate any demand
for regulation.Similarly, the extremely low amount of legal protection afforded animals in
Canada (Figure 3) could be explained by a clumsy and centralized Canadian
legislative structure that discourages prosecution, public discourse, and develop-
ment of case law (Sankoff, 2012). Similar political or cultural factors may also
explain the high level of animal use in Belgium (Figure 4).
By identifying outliers, it may be possible to determine factors that assistor hinder good animal welfare outcomes and adjust public policies accordingly.
However, these outliers aside, there is evidence that animals are better off in more
equal countries. Unlike the case with social indicators (Wilkinson & Pickett,
2010), the evidence is not overwhelming, and trends at the national level are not
repeated at the state level in the United States (Tables 2 and 3). Further researchwith more indicators is therefore necessary to confirm any effect.
It is also quite possible that the relationship between better welfare and
income equality is not causal but is related to some factor (like curtailment
of corporate power) that improves both welfare and income equality. Societies
that promote income distribution may also generally be fairer societies that alsopromote better treatment of animals.
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ACKNOWLEDGMENTS
I thank Massey University social science academic staff, Dr. Mary Murray, Dr.Srikanta Chatterjee, and Dr. Sue Cassells, and Roger Gadd for reviewing the
manuscript.
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