In this case its veganism. Now I am not a Vegan nor do I hold any opinions. I am struggling with the dichotomy of Vegan v Vegetarian v Non vegetarian. but the agenda towards a plant based and even insect based diet is being pushed by the scumbaggery. Why? Is the trend towards global cooling putting stress on the supply or is asimple case of greed. Those that control the food. anyway here is a paper pushing a Tax on red meat.
Health-motivated taxes on red and
processed meat: A modelling
study on optimal tax levels and
associated health impacts
Open AccessPeer-reviewed
Research Article
Marco Springmann,
Daniel Mason-D’Croz,
Sherman Robinson,
Keith Wiebe,
H. Charles J. Godfray,
Mike Rayner,
Peter Scarborough
Published: November 6, 2018
Abstract
Background
The consumption of red and processed meat has been
associated with increased mortality from chronic diseases,
and as a result, it has been classified by the World Health
Organization as carcinogenic (processed meat) and
probably carcinogenic (red meat) to humans. One policy
response is to regulate red and processed meat
consumption similar to other carcinogens and foods of
public health concerns. Here we describe a market-based
approach of taxing red and processed meat according to its
health impacts.
Methods
We calculated economically optimal tax levels for 149 world
regions that would account for (internalize) the health costs
associated with ill-health from red and processed meat
consumption, and we used a coupled modelling framework
to estimate the impacts of optimal taxation on consumption,
health costs, and non-communicable disease mortality.
Health impacts were estimated using a global comparative
risk assessment framework, and economic responses were
estimated using international data on health costs, prices,
and price elasticities.
Findings
The health-related costs to society attributable to red and
processed meat consumption in 2020 amounted to USD
285 billion (sensitivity intervals based on epidemiological
uncertainty (SI), 93–431), three quarters of which were due
to processed meat consumption. Under optimal taxation,
prices for processed meat increased by 25% on average,
ranging from 1% in low-income countries to over 100% in
high-income countries, and prices for red meat increased by
4%, ranging from 0.2% to over 20%. Consumption of
processed meat decreased by 16% on average, ranging
from 1% to 25%, whilst red meat consumption remained
stable as substitution for processed meat compensated
price-related reductions. The number of deaths attributable
to red and processed meat consumption decreased by 9%
(222,000; SI, 38,000–357,000), and attributable health costs
decreased by 14% (USD 41 billion; SI, 10–57) globally, in
each case with greatest reductions in high and middle-
income countries.
Interpretation
Including the social health cost of red and processed meat
consumption in the price of red and processed meat could
lead to significant health and environmental benefits, in
particular in high and middle-income countries. The optimal
tax levels estimated in this study are context-specific and
can complement the simple rules of thumb currently used
for setting health-motivated tax levels.
Competing interests: The authors have declared that no
competing interests exist.
Introduction
The consumption of red and processed meat exceeds
recommended levels in most high and middle-income
countries and has been associated with a range of negative
health and environmental impacts [1,2]. In 2015, the cancer
agency of the World Health Organization, the International
Agency for Research on Cancer (IARC), classified the
consumption of red meat, which includes beef, lamb, and
pork, as carcinogenic to humans if eaten in processed form,
and as probably carcinogenic if eaten unprocessed [3]. In
addition to being linked with cancer, the consumption of red
and processed meat has also been associated with
increased rates of coronary heart disease[4], stroke [5], type
2 diabetes mellitus [6], and overall mortality [7,8]. Those
impacts and the IARC’s classification raise the question
whether the consumption of red and processed meat should
be regulated similar to other carcinogens or to other foods of
public health concern, such as sugary drinks [9].
Market-based approaches to regulation have gained
popularity in public health research and the public debate. In
particular health-motivated taxes have been widely
discussed [10–12], and implemented in some countries, e.g.
for sugar-sweetened beverages [9,13], and saturated fats
[14]. The tax levels discussed or implemented have mostly
been based on practical considerations on their likely
impact. However, from an economic perspective, health-
motivated taxes are so-called Pigouvian taxes whose
purpose it is to correct for the unintended and previously
unaccounted consequences to society of an economic
activity (in this case, the negative health impacts associated
with red and processed meat consumption) by incorporating
the cost of those consequences into the price of the activity
or good [9,15,16]. Thus, the economically optimal tax level
of a health-motivated Pigouvian tax is determined such that
market prices include the marginal health costs of
consumption, i.e. the cost of treating the health conditions
that are associated with one additional serving of the good
in question.
Here we provide estimates of the health costs to society and
optimal tax levels for red and processed meat for all major
world regions, and we estimate the impacts that health-
motivated taxation of red and processed meat could have
on food consumption, and mortality from diet-related, non-
communicable diseases. In our analysis, we treated red
meat and processed meat as separate risk factors, and
estimated their health burden and health-motivated taxes
individually and when combined. We assumed the risk
associations between red and processed meat and diet-
related diseases as causal based on the existence of
plausible pathways, mechanistic evidence, and dose-
response relationships (see section A1 in S1 File)
[3,6,17–19]. We accounted for changes between red meat
consumption and processed meat consumption as a result
of differentiated taxation, but also for impacts on other food
groups that are considered substitutes, such as poultry, or
complements, such as vegetable oils. We focus on the year
2020 as a possible future year for implementation, and we
considered other implementation dates (2010 and 2050) in
sensitivity analyses.
Methods
We used a coupled modelling framework to calculate
optimal tax levels for red and processed meat and the
associated health and climate change impacts in the year
2020 for 149 world regions (Fig 1). Our calculation included
several steps. First, we estimated the health impacts
associated with the current and projected consumption
levels of red and processed meat. Second, we estimated
the health costs associated with those health impacts. Third,
we repeated that calculation for a scenario in which we
increased red and processed meat consumption by a
marginal increase which we take to be one additional
serving per day in each region. (Note that we are interested
in the change in mortality and health costs per marginal
increase in consumption. Because the dose-response
functions we use are linear and we divide over the marginal
increase when levying the damage costs on baseline prices,
it does not matter what we define as marginal.) Fourth, we
calculated the marginal health costs of red and processed
meat consumption by subtracting the cost estimates of the
two scenarios. Fifth, we levied the marginal health costs per
marginal change in consumption onto the initial market
prices of red and processed meat in each region, and
calculated the impacts of those price changes on
consumption levels, health impacts, and health costs.
For calculating the health impacts associated with red and
processed meat consumption, we used a global
comparative risk assessment framework [20]. We estimated
the mortality burden attributable to changes in the
consumption of red and processed meat by calculating
population attributable fractions (PAFs) which represent the
proportions of disease cases that are attributable to the risk
exposure and that would be avoided due to changes in risk
exposure, respectively [21–23]. The disease states included
coronary heart disease (CHD), stroke, colorectal cancer,
and type 2 diabetes mellitus (T2DM). There are indications
that red and processed meat consumption increases the risk
for other cancers and cardiovascular diseases [24–26]. In a
sensitivity analysis, we therefore adopted broader risk
associations of red and processed meat consumption with
total cancer and cardiovascular diseases in general Cause-specific mortality
rates and population numbers were adopted from data
reported by the Global Burden of Disease project and
projected forward using data from the United Nations
Population Division. We treated red and processed meat
consumption as two separate risk factors, and adopted the
relevant relative risk parameters describing the association
between red and processed meat consumption and
mortality from meta-analyses of prospective cohort studies
(Table A1 in S1 File) [19,4,6,5]. For calculating the joint risk
of red and processed meat consumption, we combined each
PAF mutiplicatively [21–23]. Given that the diseases
included in the modelling framework predominantly affect
adults, we focused on the health implications for individuals
aged 20 and older. In a sensitivity analysis, we estimated
the impacts that tax-related changes in food consumption
could have on weight distributions and weight-related
mortality by using derived relationships between body mass
index and food availability (Table A2 in S1 File) [20].
For estimating the health costs associated with changes in
mortality, we adopted cost-of-illness (CoI) estimates and
used a cost transfer method to estimate the costs of illness
in different parts of the world and in different years (section
A2 in S1 File) [1]. We based our cost-of-illness estimates for
CHD, stroke, and cancer on a comparative assessment of
the economic burden of CVD [27,28] and cancer [29] across
the European Union which included direct costs (healthcare
expenditure, health service utilization, expenditure on
medication) and indirect costs (opportunity costs of informal
care, productivity costs due to mortality and morbidity). We
calculated costs per death based on mortality statistics [28],
and estimated the costs per death by disease in other
regions and years by scaling the EU base values by the
ratio of health expenditure per capita for direct costs, and by
the ratio of GDP per capita (adjusted for purchasing power
parity) for indirect costs. Productivity losses due to morbidity
and mortality, which are a part of the indirect costs, were
only included for deaths occurring among those of working
age which we took to be below 65 years in all regions, in
line with other assessments [29]. For the CoI analysis
related to diabetes, we adopted country-specific cost
estimates [30], and to avoid double-counting of
complications related to cardiovascular diseases, adjusted
those for the incremental cost component specifically
attributable to diabetes [31,32]. No data was available to
estimate indirect costs for T2DM. Where possible, we
included both direct and indirect costs in our analysis in
order to account for the full health costs of red meat
consumption to society, and we explored the relative
contributions of direct and indirect costs to the final
estimates in a sensitivity analysis. On average, indirect
costs represented half to two thirds of the total cost of illness
for CHD, stroke, and cancer (Table A3 in S1 File).
For estimating the consumption feedbacks of levying taxes
on red and processed meat, we used a global agriculture-
economic model, the International Model for Policy Analysis
of Agricultural Commodities and Trade (IMPACT) [33], and
adjusted it to account for differences between red and
processed meat. The IMPACT model is based on a global
partial equilibrium multi-market model of agricultural
production, demand, trade, and prices (section A3 in S1
File). For our analysis, we adopted IMPACT data on current
and future food availability, consumer prices, and on own
and cross-price elasticities that determine how the demand
of a commodity and related commodities, such as other
types of meat, changes when its price changes [34]. To
obtain a better proxy for food consumption, we adjusted
food availability data for waste at the consumption level
using regional estimates from the Food and Agriculture
Organization of the United Nations (FAO) (section A4 in S1
File) [35], and we disaggregated total red meat consumption
into processed and unprocessed components using
compositional data from the Global Dietary Database [2].
Processed meat is generally defined as any meat preserved
by salting, curing, smoking, or by adding chemical
preservatives, including bacon, sausages, salami, hot dogs
and processed deli meats. It can also include processed
white meat, but because we disaggregate processed meat
from total red meat, we only include processed red meat
from beef, lamb and pork in our analysis. We treated red
meat and processed meat as substitutes, and used the
same cross-price elasticities that describe the substitution of
different types of meat (e.g. between beef and poultry).
Processed meats are generally cheaper than non-
processed meat, because of the quality of the parts of
meats used. In our main scenario, we used a price wedge
between processed and unprocessed meats of 15%, which
is in line with the average price difference over the last five
years in the UK [36], and we tested price wedges of zero
and 30% in a sensitivity analysis (Tables A27-A28 in S1
File). All monetary data were converted to the value of the
US dollar in 2010 by using changes in the consumer price
index by region based on data from the International
Monetary Fund.
In our uncertainty analysis, we accounted for
epidemiological and economic uncertainties. In our analysis,
the main source of epidemiological uncertainty is related to
the relative risk estimates used for calculating health
impacts, and the main source of economic uncertainty is
related to the projections of health care-related costs for
each region. In each case, we recalculated the endpoints of
our analysis (tax levels, consumption changes, health
impacts) by using the low and high values of the 95%
confidence interval of relative risk estimates, and the
standard deviation of health-cost estimates. In the main text,
we focus on the epidemiological uncertainty. Using the high
and low values of the health-cost estimates resulted in
smaller uncertainty intervals than using the high and low
values of the epidemiological uncertainty range (Tables A29-
A30 in S1 File). We also explored the impacts that changes
in price elasticities (which determine consumer responses)
have on our estimates. Varying own-price elasticities by
10%, which is in line with estimated confidence intervals
[37], also resulted in estimates within the epidemiological
uncertainty range (Tables A25-A26 in S1 File).
Results
Impacts of optimal taxation
According to our model projections (Table 1), the
consumption of red meat was associated with 860,000 (95%
confidence interval related to epidemiological uncertainty
(SI) 220–1,410,000) deaths globally in the year 2020, and
that of processed meat with 1,530,000 (SI, 430–2,470,000)
deaths. When assessed together, those represented 4.4%
of all projected deaths in the analysis in that year. About two
thirds of attributable deaths were due to stroke (for red
meat), and coronary heart disease (for processed meat),
followed by type-2 diabetes mellitus (14–17%) and
colorectal cancer (4–11%). About two thirds of attributable
deaths (64%) occurred in middle-income countries, one third
(32%) in high-income countries, and a small portion (4%) in
low-income countries. The associated costs related to
health care amounted to USD 285 billion (SI, 93–431),
which represented 0.3% of expected world GDP in that year.
More than two thirds of the health costs (69%) fell on high-
income countries (due to higher healthcare-related
expenditure), a third (30%) on middle-income countries, and
a small fraction (0.4%) on low-income countries. Country-
level results are listed in Tables A13-A14 in S1 File.
Under optimal taxation, the price for one serving of red and
processed meat reflects the health costs associated with
one additional serving of red and processed meat (Tables
A8-A9 in S1 File). Integrating the health costs associated
with one serving of red and processed meat into the prices
of one serving of red and processed meat increased the
price of red meat by 4% (SI, 1–6) on average, ranging from
less than 1% in low-income countries to 21% in high-income
countries, and the price of processed meat by 25% (SI,
10–32), ranging from 1% in low-income countries to 111% in
high-income countries (Table 1). Country-level impacts on
prices showed a greater range with price changes of up to
34% for red meat and 185% for processed meat Change in the price of red meat (a) and processed meat (b)
under cost-compensating taxation in relation to attributable
health costs (%), change in deaths attributable to red and
processed meat consumption (%) (c). We produced the
figure by mapping our data using ArcGIS (version 10.3.1,
Esri Inc.) and its layer for world countries.
https://doi.org/10.1371/journal.pone.0204139.g002
Associated with the change in prices were changes in
consumption. The greater changes in the price of processed
meat compared to red meat resulted in greater changes in
consumption for processed meat and also lead to
substitution effects, including a shift to poultry and
unprocessed red meat (despite a higher price of
unprocessed red meat in absolute), and smaller changes in
the consumption of milk and eggs, and a small decrease in
vegetable oils which is often consumed alongside meat
products (Fig 3). The consumption of processed meat
decreased by 16% (SI, 9–17; 3 g/d) on average, ranging
from 1% (0.1 g/d) in low-income countries to 25% (12 g/d) in
high-income countries (Table 1), and up to 37% (28 g/d) for
individual countries (Table A11 in S1 File). The consumption
of red meat remained similar to a situation without taxation
as a result of substitution effects, ranging from a reduction
of 0.8% to an increase of 0.7%. Other changes in
consumption were a 5% (2 g/d) increase in poultry
consumption (0.2–9% across income groups), and smaller
increases of 0.4% for milk and eggs (0–0.9% across income
groups), and a small decrease of 0.4% for vegetable oils
(0–0.9% across income groups) (Fig 3; Table A12 in S1
File).
Fig 3. Tax-related changes in food consumption by food
commodity and region.
Food commodities include processed (prcd) and
unprocessed (unprcd) red meats. Changes in food
consumption are shown in g/d, with the exception of Δkcal/d
which denotes changes in overall energy intake in terms of
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kcal/d.
https://doi.org/10.1371/journal.pone.0204139.g003
As a result of the tax-related changes in consumption, the
number of deaths attributable to red and processed meat
consumption decreased by 222,000 (SI, 38,000–357,000;
9%), from 2,400,000 (SI, 650,000–3,880,000) to 2,118,000
(SI, 609,000–3,379,000). The reductions in the number of
attributable deaths were composed of 235,000 (SI,
40,000–380,000) less deaths attributable to processed meat
consumption, and 3,200 (SI, -2,400–1,200) more deaths
attributable to red meat consumption (Table 1) (note that the
combined effect of changes in red and processed meat
consumption is generally lower than the sum of the
individual effects, because individuals can be affected by
both risks simultaneously without two types of the same
disease). The changes in attributable deaths corresponded
to a reduction in the burden attributable to red and
processed meat consumption of 9% on average, ranging
from 1% in low-income countries to 17% in high-income
countries, and up to 26% for individual countries (Fig 2C;
Table A13 in S1 File; https://doi.org/10.5287
/bodleian:j0n1Jd5rb).
Following the reduction in health burden, the healthcare-
related costs associated with red and processed meat
consumption were reduced by USD 41 billion (SI, 10–57),
from USD 285 billion (SI, 93–431) to USD 244 billion (SI,
83–374), which represented a cost reduction of 14% on
average, ranging from 1% in low-income countries to 17% in
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high-income countries (Table 1), and up to 26% for
individual countries (Table A14 in S1 File; https://doi.org
/10.5287/bodleian:j0n1Jd5rb). In comparison, tax revenues
amounted to USD 172 billion (SI, 72–215), two thirds (64%)
of which came from high-income countries, a sixth to a fifth
(16–20%) from middle-income countries, and less than 1%
from low-income countries (Table 1; Table A15 in S1 File).
Thus, healthcare-related costs under taxation exceeded tax
revenues by 42% on average, ranging from 22% in lower
middle-income countries to 50% in high-income countries.
Additional analyses
In a sensitivity analysis, we analysed a cost-compensating
taxing scheme in which we increased the prices of red and
processed meat until the tax revenues were equal to (i.e.
could pay for) the healthcare-related costs associated with
their consumption whilst taking into account the feedbacks
on consumption and health (section A5 in S1 File). Under
cost-compensating taxation, the price increases for red and
processed meat approximately doubled compared to
marginal-cost pricing, and the reductions in consumption,
attributable deaths, and healthcare-related costs of red and
processed meat increased by about a third (Table A16 in S1
File).
In addition to changes in diet-related risk factors,
consumption changes can influence weight levels and
weight-related risks associated with underweight,
overweight, and obesity [23,38]. In a sensitivity analysis, we
analysed those changes and found that the health impacts
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from tax-related changes in weight levels associated with
changes in calorie intake were small and mostly positive as
modest reductions in calorie intake reduced the number of
overweight and obese people which in most regions exceed
the number of underweight people. The weight impacts led
to an additional 3,800 (SI, 3,600–4,100) avoided deaths
globally, ranging from 9 additional deaths in low-income
countries (which compare to 860 avoided deaths due to
reduced red and processed meat consumption) to 2,900
avoided deaths in high-income countries (Tables A17-A18 in
S1 File).
Livestock-related emissions are responsible for the majority
of food-related greenhouse-gas (GHG) emissions, and for
about 14.5% of GHG emissions overall, a similar proportion
as from transport [39,40]. Consumption changes towards
lower red and processed meat consumption could therefore
have major implications for climate change. In a sensitivity
analysis, we analysed the potential changes in food-related
emissions using emissions intensities of foods obtained
from meta-analyses of life-cycle analyses (section A6 in S1
File). We note that the emissions intensities do not account
for changes in production methods and technologies that
might be associated with changes in consumption. In this
static framework, we found that optimal taxation could
reduce food-related GHG emissions by 109 MtCO2-eq (CI,
50–139), most of which due to reduced beef consumption
(Table A18 in S1 File). The change in emissions represents
a reduction of 1.2% globally, ranging from less than one
percent (0.6 MtCO2-eq) in low-income countries to 3% (62
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MtCO2-eq) in high-income countries, and up to 7% in
individual countries (Tables A19-A20 in S1 File).
Red and processed meat consumption is expected to
increase in the future, in particular in low and middle-income
countries [41,42]. Increases in red and processed meat
consumption have implications for optimal tax levels when
associated with changes in disease-specific mortality rates
and healthcare-related costs. In a final sensitivity analysis,
we projected optimal taxes on red and processed meat for
the year 2050. As a consequence of socio-economic
changes and changes in healthcare-related costs, we found
that optimal tax rates more than doubled, ranging from two-
fold increases in high-income countries to five-fold increases
in low-income countries (Table A21 in S1 File).
Discussion
The consumption of red and processed meat has been
associated with increased mortality from chronic diseases,
and red and processed meat have been declared by the
World Health Organization to be carcinogenic (processed
meat) and probably carcinogenic (red meat) to humans
[3–6,17,19,24,25]. One possible policy response to these
impacts is market-based regulation in the form of taxes.
Here we estimated optimal tax levels for red and processed
meat that are based on the (marginal) health cost
associated with red and processed meat consumption. By
design, the level of health-motivated taxes is context-
specific and accounts for disease-specific health costs and
mortality in a given location. Consequently, we find that
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health-motivated taxation of red and processed meat would
be low in low-income countries which currently experience a
low health and economic burden from red and processed
meat consumption, and taxation would be high in high and
middle-income countries which currently experience a
greater health and economic burden. As income is projected
to increase in future years, in particular in low and middle-
income countries, it can be expected that optimal tax levels
would increase in line with dietary and socio-economic
changes.
In our analysis, we estimated a health burden associated
with red and processed meat consumption of 2.4 (SI,
0.7–3.9) million attributable deaths in 2020, which
represented 4.4% of all projected deaths in the analysis in
that year. For the year 2010, the estimates of the number of
deaths attributable to red and processed meat consumption
are 2.0 (SI, 0.5–3.2) million (Table A22 in S1 File). Our
estimates are more comprehensive than the Global Burden
of Disease estimate of 0.9 (95% confidence interval (CI),
0.2–1.5) million deaths attributable to red and processed
meat in 2010 [22], and 0.7 (CI, 0.6–1.0) million deaths in
2013 [23]. Compared to the GBD estimates, we considered
a greater number of disease associations of red and
processed meat consumption (CHD, stroke, colorectal
cancer, and T2DM compared to CHD, colorectal cancer and
T2DM), and we considered minimal exposure levels of zero
instead of 11·4–17·1 g/d for red meat and 0–14·3 g/d for
processed meat assumed for the GBD estimate for 2013
[22,23]. Both choices are supported by epidemiological
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evidence (see section A1 in S1 File for a more
comprehensive discussion) [43,7,25,24]. Another difference
is that we used consumption data that is not standardised to
an energy intake of 2000 kcal/d, something that accounts for
over and underconsumption. Our analysis might therefore
reflect more accurately absolute consumption levels than
one based on the energy-standardised data of food
composition used by the GBD. Harmonising risk factors,
minimum exposures, and energy intake reduced the
difference between the GBD estimate and ours from 170%
to 78% (risk factors), 72% (risk factors and minimum
exposure), 47% (risk factors and energy intake), and 41%
(risk factors, minimum exposure, and energy intake),
respectively, with overlapping confidence intervals (Table
A23 in S1 File).
We estimated an economic burden associated with red and
processed meat consumption of USD 285 billion (SI,
93–431) in 2020, which represented 0.3% of the total health
expenditure estimated for that year. Our estimate included
both direct costs (healthcare expenditure, health service
utilization, expenditure on medication) and indirect costs
(opportunity costs of informal care, productivity costs due to
mortality and morbidity) to provide an estimate of the full
health costs of red and processed meat consumption to
society. On average, indirect costs represented half to two
thirds of the total cost of illness for CHD, stroke, and cancer,
but no estimates of indirect costs were available for T2DM.
Our estimate of the economic burden attributable to red and
processed meat consumption can therefore be considered
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an underestimate of all costs. Focusing only on the direct
cost component would roughly half our estimate (Table A24
in S1 File), and using a more general valuation approach
based on a measure for the willingness to pay for a
reduction in mortality risk, the so-called value-of-statistical-
life approach, would increase our estimate by about a factor
of ten [1]. Using disease associations for total cancer
(instead of colorectal cancer only) and cardiovascular
disease (instead of CHD and stroke only) would roughly
double the health and economic burden (Table A23 in S1
File).
Our analysis highlights significant differences between the
tax-related impacts on the prices and consumption of red
and processed meat. For example, in order to account for
the health costs attributable to red and processed meat by
adjusting prices, red meat prices would have to increase by
more than 20% in high-income countries, and processed
meat prices would have to more than double for those
countries. Price changes in upper middle-income countries
would amount to 7% and 47% for red meat and processed
meat, respectively. As a result, processed meat
consumption would decrease by about one serving per
week (12 g/d) in high-income countries and less than a third
of a serving per week (4 g/d) in upper middle-income
countries. As consumers are projected to partially switch
from processed meat to unprocessed meat and other
substitutes such as poultry, red meat consumption would
remain largely unchanged in those regions despite its
increase price. The total reduction in red and processed
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meat consumption is therefore lower than one would expect
based on the associated changes in prices. Although the
changes in red and processed meat consumption are still
substantial on a population level, absolute levels of red and
processed meat consumption would remain higher in each
region (130 g/d in high-income countries and 88 g/d in upper
middle-income countries) than recommended by bodies
such as the World Cancer Research Institute, which advises
consumption of less than 300 g of (uncooked) red meat per
week (about 40 g/d), little if any in processed form [26].
Market-based approaches, such as health-motivated
taxation, can therefore best be considered as one of a range
of measures that would be needed to move diets towards
more healthy and sustainable consumption patterns [44].
With respect to the environmental co-benefits of health
motivated taxation of red and processed meat, we estimated
an emissions reduction potential of about 110 MtCO2-eq
globally in 2020, in absence of changes in production
methods and technologies that might be associated with
changes in consumption. The change in emissions
represented a reduction in food-related GHG emissions of
1.2%. The reduction potential is similar to that of technical
greenhouse-gas mitigation options, such as rice, livestock,
and manure management, which have been estimated to be
below 250 MtCO2-eq each [45,46]. Thus, health-motivated
taxation of red and processed meat, alongside other
measures, could make meaningful contributions to food-
related emissions-reduction targets [47]. In another study,
we estimated the mitigation potential of environmentally
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motivated taxation of foods in general to be up to 1 GtCO2-
eq in 2020 [48]. However, in environmentally motivated
taxation schemes, we found that care has to be taken to
compensate for potential reductions in food security, e.g. by
using tax revenues for health promotion measures, whereas
in the health-motivated approach analysed here, health
concerns are built into by design, but all red meat (beef,
lamb, pork) is treated equally despite differing emissions
intensities. How to optimally combine health and
environmentally motivated schemes remains an important
question for future research.
Several caveats apply. We assumed that the risk
associations between red and processed meat and diet-
related diseases are causal based on mechanistic evidence
from analyses of the digestive tract for colorectal cancer [3],
there are several pathways that plausibly explain the
increase in risk for other disease [6,17–19], and the disease
associations show a dose-response relationship in cohort
studies [17–19]. Whilst the cohort studies controlled for
major confounding factors, such as body mass and
smoking, we cannot rule out a residual effect of other
confounding risk factors. We did not track changes in the
nutritional quality of diets, such as levels of micronutrients
that could be of concern especially in low-income countries.
However, our analysis suggests that cost-compensating tax
levels would be zero or close to zero in such environments,
and the magnitude of estimated changes is unlikely to have
any detrimental impacts in high and middle-income
environments where most micronutrient levels are adequate
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and can be easily obtained from other sources [49]. Due to
our focus on consumption, we did not analyse the
implications for agricultural production, livelihoods, market
adjustments between countries and across time, or how
health systems might change under different funding
schemes. We hope our comparative regional analysis
provides a good starting point for such research.
In our analysis of consumption changes, we used a set of
regionally comparable own and cross-price elasticities that
describe the substitution between different animal-based
foods, and between animal-based foods and some
complementary foods, such as vegetable oils. Such
substitution is in line with recent reviews of country-level
data [50]. However, we cannot rule out substitution effects
not captured by the data, such as replacement of processed
meat with fish, legumes or grains, especially when changes
in caloric intake would be substantial. Both our health
estimates and our emissions estimates would change
depending on the food groups that would compensate for
the reductions in processed meat consumption. For
example, greater consumption of sugar and refined
carbohydrates, something that is associated with negative
health impacts [51], could compensate some of the health
benefits associated with lower consumption of processed
meat. Similarly, a switch from beef to fish caught by trawling
could offset a portion of the emissions reductions associated
with reduced processed meat consumption [52]. On the
other hand, replacement of red and processed meat with
legumes, fruits and vegetables, or whole grains could lead
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to additional health benefits without significantly affecting
the emissions reductions identified here [23,51,52].
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