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R E S E A R C H Open Access
Reducing our environmental footprint and
improving our health: greenhouse gas emission
and land use of usual diet and mortality in
EPIC-NL: a prospective cohort study
Sander Biesbroek
1
, H Bas Bueno-de-Mesquita
1,2,3
, Petra HM Peeters
3,4
, WM Monique Verschuren
1
,
Yvonne T van der Schouw
4
, Gerard FH Kramer
5
, Marcelo Tyszler
5,6
and Elisabeth HM Temme
1*
Abstract
Background: Food choices influence health status, but also have a great impact on the environment. The production
of animal-derived foods has a high environmental burden, whereas the burden of refined carbohydrates, vegetables
and fruit is low. The aim of this study was to investigate the associations of greenhouse gas emission (GHGE) and land
use of usual diet with mortality risk, and to estimate the effect of a modelled meat substitution scenario on health and
the environment.
Methods: The usual diet of 40011 subjects in the EPIC-NL cohort was assessed using a food frequency questionnaire.
GHGE and land use of food products were based on life cycle analysis. Cox proportional hazard ratios (HR) were
calculated to determine relative mortality risk. In the modelled meat-substitution scenario, one-third (35 gram) of the
usual daily meat intake (105 gram) was substituted by other foods.
Results: During a follow-up of 15.9 years, 2563 deaths were registered. GHGE and land use of the usual diet were not
associated with all-cause or with cause-specific mortality. Highest vs. lowest quartile of GHGE and land use adjusted
hazard ratios for all-cause mortality were respectively 1.00 (95% CI: 0.86-1.17) and 1.05 (95% CI: 0.89-1.23). Modelled
substitution of 35 g/d of meat with vegetables, fruit-nuts-seeds, pasta-rice-couscous, or fish significantly increased
survival rates (6-19%), reduced GHGE (4-11%), and land use (10-12%).
Conclusions: There were no significant associations observed between dietary-derived GHGE and land use and
mortality in this Dutch cohort. However, the scenario-study showed that substitution of meat with other major food
groups was associated with a lower mortality risk and a reduced environmental burden. Especially when vegetables,
fruit-nuts-seeds, fish, or pasta-rice-couscous replaced meat.
Keywords: Sustainability, Diet, Greenhouse gas emission, Land use, Health, Mortality, EPIC-NL, Prospective studies,
Environmental impact, Substitution scenarios
* Correspondence: liesbeth.temme@rivm.nl
1
Centre for Nutrition, Prevention and Health Services, The National Institute
for Public Health and the Environment (RIVM), Antonie van Leeuwenhoek 9,
Bilthoven 3721 MA, The Netherlands
Full list of author information is available at the end of the article
© 2014 Biesbroek et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.
Biesbroek et al. Environmental Health 2014, 13:27
http://www.ehjournal.net/content/13/1/27
Background
Current climate changes and the increased need for food
underlines the importance of a sustainable food system [1].
Food choices influence health status, but also have a great
impact on the environment through food production. Cur-
rently, the contribution of food production and consump-
tion to the European Union’s total greenhouse gas emission
(GHGE) is approximately 20-30% [2]. Individuals can dir-
ectly influence this share via their own choice of food.
The largest environmental impact from food comes
from the production and consumption of meat and dairy
products; the estimated GHGE is 50% and use of total
farmlands is 80% [3-5]. Meat and dairy products also sup-
ply about one-third of the dietary energy intake and are
major sources of saturated fatty acids in the diet. Diets
high in animal products and low in vegetables and fruits,
like the Western diet, are associated with a higher risk of
major chronic diseases [6-8]. A comparison between a
meat-based and a lactoovovegetarian diet also showed that
the typical Western diet is less sustainable [9].
A diet according to the Dutch national dietary guide-
lines would result in a 8% reduction in GHGE (men 13%,
women 3%) when compared to the actual dietary pattern
as observed in the Dutch national food consumption sur-
vey [3]. The dietary guidelines, established in 2006, pro-
mote a varied diet with plenty of fruit, vegetables and
whole-grain cereal products [10]. A study from the UK
modelled the health effects of three diets with a different
carbon footprint reduction [11]. The results showed that a
modelled 50% reduction of meat and dairy products iso-
calorically replaced by vegetables, fruit, and cereals re-
sulted in the highest GHGE reduction and most deaths
delayed or averted per year. Another recent UK study in-
vestigated how consumer’s food choice could reduce food-
derived GHGE [12]. Results showed a potential GHGE
reduction of 35% if meat products were completely elimi-
nated from the diet and 12% when avoidable food waste
was cut out. Not eating foods grown in greenhouses or
airfreighted to the UK could lead to another 5% reduction.
Vieux et al. showed that when total caloric intake is re-
duced to meet the average individual’s energy needs, the
diet-associated GHGE decreased between 2-11% [13]. In
addition, when meat was iso-calorically substituted by fruit
and vegetables either null or even positive diet-associated
GHGE variations occurred. A modelled substitution of
animal-derived food products by plant-derived food prod-
ucts resulted in substantial reductions of GHGE and land
use [14,15] and a lower risk for all-cause mortality and cor-
onary heart disease [16,17].
Although it is expected that a diet which is environmen-
tal friendlier also reduces mortality of chronic diseases,
this has never been investigated in a real-life setting.
Therefore, the aim of this study was to investigate to what
extent an environmental friendlier diet is also a healthier
diet by increasing survival rates in the EPIC-NL cohort
study. The effects of food weight-based modelled substitu-
tion scenarios, in which part of the total meat intake was
replaced by other food groups, on mortality and environ-
mental impact were also investigated.
Methods
Study population
EPIC-NL is the Dutch contribution to European Prospect-
ive Investigation into Cancer and Nutrition [18]. EPIC-NL
consists of 40 011 subjects of PROSPECT and MORGEN.
The PROSPECT cohort included 17 357 women aged 49–
70 years, participating in the national breast cancer screen-
ing program and living in the city of Utrecht and its
surroundings [19]. The MORGEN cohort included 22 654
men and women aged 20–59 years, selected from ran-
dom samples of the Dutch population in Amsterdam,
Doetinchem, and Maastricht [20,21]. Both cohorts com-
ply with the Declaration of Helsinki.
Exclusion criteria for the present analyses were no in-
formed consent for follow-up of vital status (n = 956) and
missing follow-up data (n = 16). Participants with a history
of cancer (n = 1640), diabetes (n = 781), myocardial infarc-
tion (n = 536), stroke (n = 458), or a combination of these
diseases (n = 249) were excluded because the usual diet re-
ported by these persons may not reflect their diet before
diagnosis. In addition, these participants have a higher risk
of death. Subjects without dietary information (n = 154)
were excluded. To exclude implausible values, participants
in the highest and lowest 0.5% of the ratio of reported en-
ergy intake (based on the food frequency questionnaire
(FFQ)) on energy requirement (estimated on the basis of
basal metabolic rate (BMR)) were also excluded (n = 662).
After these exclusions, 35 057 participants remained for
the all-cause mortality survival analysis.
Diet and environmental impact assessment
Usual daily dietary intake was estimated by a 178-item
FFQ that has been validated against twelve 24-h recalls,
and biomarkers in 24-h urine and blood [22,23]. Spearman
rank correlation coefficients based on estimates of the
FFQ and 24-h recalls were 0.51 for potatoes, 0.36 for vege-
tables, 0.68 for fruits, 0.39 for meat, 0.69 for dairy, 0.76 for
sugar and sweet products, and 0.52 for biscuits and pastry
in men. Results for women were similar.
Blonk Consultants assessed the environmental impact of
the Dutch dietary habits [3]. To estimate sustainability
scores, life cycle assessments (LCA) were performed for
254 food items. The LCA’s were cradle to grave and in-
cluded production, processing, packaging, transport, stor-
age, preparation, cooking, avoidable and unavoidable food
waste (inedible parts) at home, and waste incineration.
GHGE covers carbon dioxide (C0
2
) emissions through the
use of fossil fuels, methane (CH
4
) released during the
Biesbroek et al. Environmental Health 2014, 13:27 Page 2 of 9
http://www.ehjournal.net/content/13/1/27
rearing of cattle and the cultivation of certain crops, and
nitrous oxide (N
2
0) released from fertilizers, manure and
ploughing of grassland [24,25]. GHGE is expressed as kg
CO
2
-equivalents per day. Land use covers the surface
needed for the production of food [24,25] and is expressed
as m
2
*year per day. These LCA data were combined with
the EPIC-NL FFQ data to calculate individual daily green-
house gas emission and land use for each of our partici-
pants. The LCA scores were based on current production
practices and assumed equal in the nineties when the FFQ
was assessed.
Participants characteristics
At baseline, study participants completed a questionnaire
on the presence of chronic diseases and related potential
risk factors, and medical and lifestyle factors [18]. Body
mass index (BMI) was calculated by dividing weight by
height squared. Educational level was coded in low (lower
vocational training or primary school), medium (intermedi-
ate vocational training or secondary school), or high (higher
vocational training or university). The smoking of ciga-
rettes, pipe, or cigars was categorized as current, former,
and never. Physical activity was assessed with the validated
Cambridge Physical Activity Score (CPAI) [26].
Mortality assessment
Vital status of all EPIC-NL participants was obtained
through linkage with the municipal population registries.
The information on vital status for the EPIC-NL cohort is
complete until 11 April 2011 for MORGEN and until 4
July 2011 for PROSPECT. These data were retrieved from
the GBA (Dutch Municipality Basic Administration).
Participants were followed fortheoccurrenceofcan-
cer, cardiovascular disease, respiratory disease and other
causes by linkage to several disease registries (Dutch
Cancer Registry and Dutch Hospital Discharge Diagno-
sis Database). Primary cause of death was coded accord-
ing to the International Classification of Diseases (ICD).
Incidence of cancer deaths was coded as 140–239 (ICD-9)
or C00-D48 (ICD-10), incidence of cardiovascular disease
(CVD) deaths as 390–459 (ICD-9) or I00-I99 (ICD-10), in-
cidence of respiratory system disease mortality as 460–519
(ICD-9) or J00-J99 (ICD-10). The remaining causes of
death were merged into the category ‘other causes’.
Cause-specific mortality data were available until 31
December 2010. This is the most recent linkage to the
database of Statistics Netherlands.
Statistical analysis
Participants were followed over time until death from any
cause, loss to follow-up, or were censored on 11 April
2011 for MORGEN and 4 July 2011 for PROSPECT. In
the cause-specific mortality analysis, the censor date was
31 December 2010 for both cohorts.
Cox proportional hazard models were used to estimate
crude and adjusted hazard ratios (HRs) with 95% confi-
dence intervals (CI) for GHGE and land use in associ-
ation with mortality. Using manual backward selection,
covariates were excluded from the final model when the
HR did not change ≥10% [27]. This manual selection
was performed because no other prospective studies in-
vestigated the effect of the environmental impact of the
diet, and therefore, there are no established confounders.
The covariates BMI, educational level, smoking habits,
physical activity, alcohol intake, and waist circumference
were omitted from the final model whereas age and
gender were retained. The covariate age failed to meet
the proportional hazards assumption according to the
Schoenfeld residuals test (p < 0.0001). Adjusted models
were Cox stratified by age (continuous) to correct for this.
To test for linear trends across categories, we modelled
GHGE and land use by including the median value of each
quartile as a continuous variable. By adding interaction
terms to the model, we assessed deviation from multi-
plicative interaction for age, sex, BMI, smoking, and waist
circumference. None of these factors modified the studied
association. A test model in which quartiles of exposure
were created from total GHGE and land use divided by
total energy intake, GHGE/kJ and m
2
/kJ, showed very
similar results (results not shown).
To study the effect of a modelled substitution of meat
by other food components, both meat and the replace-
ment component were added as continuous variables in
the same multivariate model. Similar to previous studies,
the difference in the parameter estimates and covariance
was used to estimate HR and 95% CI [16,17]. The models
were adjusted for major dietary and lifestyle factors (age,
gender, BMI, smoking status, physical activity, energy in-
take, and alcohol intake). The investigated substitution
component sources were potatoes, total vegetables, total
fruit-nuts-seeds, pasta-rice-couscous, cheese, milk-based
desserts, or fish. These food groups were selected because
they can replace meat in a hot meal. In addition, they rep-
resent highly acceptable food products that are consumed
in significant amounts in the current Dutch diet (Tables 1
and 2), and thus represent acceptable substitutions for
meat. The modelled substitution was a one-third reduc-
tion (35-gram) of the average (105-gram, standard devi-
ation of 55-gram) total daily meat intake in EPIC-NL. For
realistic scenarios, we substituted by equal food weight
and not the same amount of dietary energy. For example,
in case of applying iso-caloric substitutions, an additional
300 gram of vegetables is needed to compensate for the
energy intake of 35 gram of meat and this was assumed
not to be realistic. Another argument for substitution
based on food weight is that a large part of the adult
Dutch population is overweight. This suggests that energy
intake is high compared with energy requirements. Effects
Biesbroek et al. Environmental Health 2014, 13:27 Page 3 of 9
http://www.ehjournal.net/content/13/1/27
on environmental impact were based on the food group
average GHGE and land use. The average environmental
impact of meat was based on the proportional daily intake,
i.e. non-processed meat accounts for 80% of total gram
per day intake of meat.
All statistical analyses were performed using SAS soft-
ware (version 9.3, SAS Institute Inc., Cary, NC, USA). A
two-sided p-value of <0.05 was considered statistically
significant.
Results
During a median follow-up of 15.9 years, 2563 deaths were
registered. The observed EPIC-NL cohort median value of
GHGE was 3.87 kg CO
2
-equivalents/d and for land use
3.61 m
2
*year/d. While contributing 3.6% of daily intake
weight (and 11% of daily energy intake), total meat intake
accounts for approximately 30% of total dietary-derived
GHGE and land use (Table 1). The impact of dairy and
beverage consumption on the environment is substantial
(dairy: 25% of GHGE and 17% of land use; beverages: 13%
of GHGE and 16% of land use).
A higher energy, vegetables, fruits, dairy, meat, cereals,
fat, soups, and alcohol intake, a lower age, an increased
proportion of men, smokers, and higher activity level
were associated with a higher environmental impact of
usual diet. Educational level, waist to hip ratio, and body
mass index (BMI) differed only slightly between the
highest and lowest quartiles of GHGE and land use
(Table 2).
In the crude Cox proportional hazards analyses, we ob-
served an inverse association of total greenhouse gas emis-
sion of usual diet with all-cause mortality. The HR (95%
confidence interval) of highest versus lowest quartile of
GHGE was 0.76 (0.68-0.85) (Table 3). After multivariable
adjustment, model 1, no association with risk was seen
(HR of 1.00 (0.86-1.17)). Additional adjustment for energy
intake, model 2, did not change the association. The find-
ings from the fully adjusted model, all possible con-
founders included, were essentially similar to the sparsely
adjusted model (model 1). Hazard ratios of highest versus
lowest quartile of GHGE for adjusted cause-specific mor-
tality models were for cancer 1.01 (0.86-1.34), CVD 0.90
(0.63-1.28), 1.12 (0.52-2.39) for respiratory diseases, and
0.91 (0.64-1.30) for other causes of death.
In crude analysis, total land use of usual diet was in-
versely associated with all-cause mortality (HR of highest
versus lowest quartile: 0.74 (0.66-0.82)) (Table 4). How-
ever, after multivariable adjustment, we found a statisti-
cally non-significant HR of 1.05 (0.89-1.23). Correction for
energy intake did not alter the association. Cause-specific
adjusted HR’s were 1.10 (0.88-1.37) for cancer, 1.07 (0.75-
1.54) for CVD, 1.19 (0.58-2.46) for respiratory diseases,
and 0.88 (0.61-1.27) for deaths by remaining causes.
Modelling a substitution of 35 g/d of total meat intake
by an equal amount of potatoes, pasta-rice-couscous, veg-
etables, fruit-nuts-seeds, milk-based desserts, fish, or
cheese has environmental or health benefits (table 5). Re-
ductions in total daily greenhouse gas emissions were
10.8% for potatoes, 10.1% for pasta-rice-couscous, 10.0%
for vegetables, 10.0% for fruits-nuts-seeds, 10.0% for milk-
based desserts, 4.5% for fish, 0.6% for cheese, and 11.5%
for reducing meat intake by 35 gram without replacements
based on the average carbon footprint of the usual diet in
EPIC-NL. Reductions in land use were 11.3% for potatoes,
9.7% for pasta-rice-couscous, 10.8% for vegetables, and
10.3% for fruit-nuts-seeds, 10.9% for milk-based desserts,
9.8% for fish, 4.5% for cheese, and 11.7% without any re-
placement. In addition, favourable health effects of the
substitutions were observed. When compared, 35 gram of
pasta-rice-couscous instead of meat was associated with
an 11% (95% CI, 4% to 16%) lower risk. A substitution by
vegetables was associated with a 9% (95% CI, 3% to 15%)
Table 1 Contribution of different food groups to daily
intake and environmental impact in EPIC-NL
Food group Gram/d (%) C0
2
–eq (%) Land use (%)
Potatoes 3.5 1.9 1.2
Vegetables 4.4 5.5 3.6
Legumes 0.3 0.3 0.3
Fruit, nuts and seeds 6.9 5.6 4.4
Dairy
Cheese 1.3 11.6 7.7
Milk
a
9.4 9.5 6.5
Milk-based desserts
b
3.5 4.1 2.6
Meat
Non-processed meat
c
2.5 25.7 28.1
Processed meat
d
1.1 5.6 6.1
Cereals
Bread products 5.0 3.4 4.8
Pasta, rice and couscous 1.6 1.5 2.6
Fish 0.4 2.1 0.8
Egg 0.5 1.2 1.8
Fat 0.9 2.3 5.0
Sugar and confectionary 1.5 2.5 1.7
Cake and biscuits 1.0 2.1 3.6
Beverages
Non-alcoholic 48.0 9.4 10.9
Alcoholic 4.8 3.4 5.1
Condiments and sauces 0.7 0.8 1.2
Soups 2.4 0.6 0.2
Miscellaneous 0.3 2.1 2.0
a
consists of milk, milk beverages (chocolate milk), and coffee milk;
b
consists of
(fruit)yoghurt, cream desserts, and milk-based puddings;
c
non-processed meat:
beef, pork, and chicken;
d
processed meat: liver-containing items, ham, and
miscellaneous types.
Biesbroek et al. Environmental Health 2014, 13:27 Page 4 of 9
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lower risk of all-cause mortality and by fruit-nuts-seeds
with a 6% (95% CI, 1% to 10%) lower risk. A shift to 35
gram more milk-based dessert was associated with a bor-
derline non-significant 4% (95% CI, 0% to 9%) lower risk.
Substitution by fish was associated with a 19% (95% CI,
3% to 33%) lower risk. 35 gram more cheese instead of
meat (HR: 6% (95% CI, −4% to 14%)) or potatoes (HR: 0%
(95% CI, −6% to 7%)) was not associated with a lower all-
cause mortality risk. Reducing intake of total meat by 35
gram without replacement was associated with a 4% (95%
CI, 2% to 7%) lower mortality risk.
Discussion
In this large prospective cohort of Dutch men and
women, we observed that the total environmental im-
pact of usual diet was not associated with all-cause or
cause-specific mortality. This indicates that an environ-
mental friendlier diet is not necessarily a healthier diet.
Table 2 Baseline characteristics by dietary greenhouse gas emission and land use in EPIC-NL
Greenhouse gas emission (CO
2
-eq/d) Land use (m
2
*year/d)
Characteristic Quartile 1 <3.26 Quartile 4 >4.56 Quartile 1 <2.99 Quartile 4 >4.28
No. of subjects 8770 8769 8769 8769
No. of deaths
a
736 (8.4) 570 (6.5) 741 (8.5) 558 (6.4)
Person-years
b
15.8 (14.6-17.0) 16.0 (14.7-17.2) 15.8 (14.6-16.9) 16.0 (14.7-17.2)
GHGE
b,c
2.86 (2.56-3.07) 5.12 (4.79-5.62) 2.84 (2.55-3.14) 5.10 (4.71-5.62)
Land use
b, d
2.62 (2.31-2.88) 4.78 (4.42-5.28) 2.61 (2.31-2.82) 4.80 (4.51-5.28)
Age (years)
b
52 (44–59) 48 (37–54) 53 (44–60) 48 (37–54)
Male gender
a
896 (10.2) 4521 (51.6) 766 (8.7) 4727 (53.9)
BMI (kg/m
2
)
b
24.8 (22.4-27.1) 25.5 (23.2-28.0) 24.7 (22.3-27.0) 25.5 (23.2-28.0)
High education level
a,e
1601 (18.4) 2025 (23.3) 1640 (18.8) 2141 (24.6)
Current smokers
a
2466 (28.2) 3086 (35.3) 2179 (25.0) 2607 (29.8)
CPAI-‘active’
a,f
3249 (37.1) 2488 (48.2) 3379 (38.5) 4070 (46.4)
Waist circumference (cm)
b
81.0 (74.3-89.0) 87.3 (80.0-95.8) 81.0 (74.0-89.0) 87.8 (80.0-96.0)
Energy intake (MJ)
b
6.4 (5.6-7.3) 11.0 (9.4-12.8) 6.4 (5.6-7.4) 10.9 (9.43-12.8)
Ratio EI/BMR
b,g
1.1 (1.0-1.3) 1.6 (1.4-1.9) 1.1 (1.0-1.3) 1.6 (1.4-1.9)
Alcohol use (g)
b
2.1 (0.2-9.1) 10.3 (2.2-24.0) 1.5 (0.1-6.6) 12.9 (3.5-28.0)
Dietary intake
b
Potatoes 69 (41–105) 122 (75–179) 66 (41–101) 123 (76–180)
Vegetables 108 (82–140) 138 (107–175) 111 (84–145) 134 (105–171)
Legumes 5 (2–11) 8 (3–15) 5 (2–11) 8 (3–15)
Fruit, nuts & seeds 142 (92–250) 192 (118–300) 171 (109–262) 170 (104–274)
Dairy 261 (143–402) 533 (321–763) 308 (171–466) 453 (258–683)
Non-processed meat
h
41 (23–58) 99 (84–125) 36 (21–51) 101 (87–126)
Processed meat
i
15 (6–27) 40 (22–48) 14 (5–23) 43 (25–67)
Cereals 148 (11–193) 233 (171–311) 147 (111–191) 238 (174–315)
Fish 6 (2–14) 10 (−17) 7 (2–14) 9 (4–16)
Egg 11 (5–18) 16 (9–29) 11 (5–18) 17 (10–29)
Fat 20 (13–28) 34 (23–48) 19 (12–27) 36 (24–49)
Sugar & confectionary 31 (17–50) 48 (27–76) 31 (18–50) 47 (25–76)
Cake & biscuits 22 (11–37) 27 (14–45) 22 (11–37) 26 (13–44)
Beverages 1325 (1041–1670) 1717 (1368–2140) 1327 (1038–1678) 1726 (1395–2135)
Condiments & sauces 12 (5–22) 22 (11–33) 11 (5–22) 23 (12–34)
Soups 36 (17–72) 72 (33–107) 36 (17–72) 72 (33–107)
Miscellaneous 5 (2–11) 7 (3–15) 6 (2–11) 8 (4–15)
a
Values displayed as frequency (percentage);
b
Values displayed as median with interquartile range (25-75
th
percentile);
c
GHGE: greenhouse gas emission (C0
2
-eq/d);
d
Land use (m
2
*year/d);
e
college or university degree;
f
Cambridge Physical Activity Score (inactive, moderately inactive, moderately active, active);
g
Ratio of energy intake
(EI) and basal metabolic rate (BMR);
h
non-processed meat: beef, pork, and chicken;
i
processed meat: liver-containing items, ham, and miscellaneous types.
Biesbroek et al. Environmental Health 2014, 13:27 Page 5 of 9
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Even though meat only contributed for 3.6% to the total
weight of daily intake in grams, it is responsible for ap-
proximately 30% of dietary greenhouse gas emission and
land use. A 35 g/d reduction or shift from total meat in-
take to vegetables, fruit-nuts-seeds, pasta-rice-couscous,
or fish would significantly increase survival rates (4-19%),
reduce GHGE (4-12%), and land use (10-12%).
In this study, the environmental burden of the usual
diet was divided into quartiles of total GHGE and land
use to analyse the influence of diets with a higher impact
on the relative risk for mortality. For this division no im-
pact on mortality risk was observed in the Cox survival
models. Other studies have suggested that a healthier
diet may also be more sustainable [3,15]. A diet accord-
ing to the Dutch Dietary Guidelines would result in 8%
less GHGE and decrease land use by 21% compared to
the average diet. However, a healthier diet and diet with
a lower environmental impact do not necessarily need to
be equally sustainable. For example, a healthy diet that
includes fruits and vegetables with a high GHGE, rice
instead of pasta or potatoes and more meat has twice
the GHGE compared to an equally healthy low-GHGE
diet [28]. On the other hand, a less healthy diet, with
high quantities of sugars and refined carbohydrates,
small quantities of meat, fruits and vegetables, can also
have a low GHGE. Our modelled substitution scenario
resulted in healthier diets with reduced environmental
impact. Substitutions of meat lead to a double benefit in
both health and reduced environmental impact aspects.
However, a healthier diet is not necessarily accompan-
ied by a lower GHGE or less land use.
The Dutch diet is relatively high in animal-derived prod-
ucts and refined carbohydrates and low in fruit and vege-
tables. Within the dietary range of this cohort, there was
no significant association between the overall daily GHGE
and land use and mortality. Although total GHGE and
land use were not associated with mortality, modelling a
one-third reduction of total meat, a major contributor to
dietary GHGE and land use, resulted in both reduced
mortality risk as well as reduced environmental impact.
Table 3 Data for mortality risks according to greenhouse gas emissions of usual diet in EPIC-NL
Greenhouse gas emission (CO
2
-eq/d) Pfor
linear trend
<3.26 3.26 - 3.87 3.87 - 4.56 >4.56
All-cause mortality
No. of participants 8770 8769 8771 8769
No. of deaths 736 671 586 570
Person-years, median 15.8 15.9 15.8 16.0
Crude HR
a
(95% CI) 1 (REF) 0.90 (0.81-1.00) 0.79 (0.71-0.88) 0.76 (0.68-0.85) P< 0.0001
d
Model 1
b
HR 1 0.97 (0.84-1.12) 0.90 (0.77-1.05) 1.00 (0.86-1.17) P= 0.7959
Model 2
b,c
HR 1 0.96 (0.82-1.11) 0.87 (0.74-1.03) 0.95 (0.77-1.15) P= 0.4266
Cause-specific mortality
Cancer
No. of deaths 327 324 274 268
Crude HR
a
(95% CI) 1 (REF) 0.99 (0.85-1.15) 0.83 (0.71-0.98) 0.81 (0.69-0.96) P= 0.0031
d
Model 1
b
HR 1 1.01 (0.89-1.33) 0.93 (0.75-1.16) 1.01 (0.86-1.34) P= 0.7654
CVD
No. of deaths 164 146 115 120
Crude HR
a
(95% CI) 1 (REF) 0.89 (0.71-1.11) 0.70 (0.55-0.89) 0.73 (0.57-0.92) P= 0.0023
d
Model 1
b
HR 1 0.92 (0.67-1.26) 0.83 (0.59-1.17) 0.90 (0.63-1.28) P= 0.4681
Respiratory diseases
No. of deaths 41 37 32 27
Crude HR
a
(95% CI) 1 (REF) 0.90 (0.58-1.40) 0.78 (0.79-1.23) 0.65 (0.40-1.06) P= 0.0687
Model 1
b
HR 1 1.01 (0.53-1.91) 0.76 (0.39-1.49) 1.12 (0.52-2.39) P= 0.9945
Other causes
No. of deaths 157 124 128 120
Crude HR
a
(95% CI) 1 (REF) 0.79 (0.62-0.99) 0.81 (0.64-1.02) 0.76 (0.60-0.96) P= 0.0334
d
Model 1
b
HR 1 0.83 (0.59-1.15) 0.96 (0.68-1.35) 0.91 (0.64-1.30) P= 0.7902
a
HR: hazard ratio;
b
Cox stratified for age (continuous) and adjusted for sex;
c
Additional adjusted for energy intake.
d
p value for linear trend significant (p < 0.05).
Biesbroek et al. Environmental Health 2014, 13:27 Page 6 of 9
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The 35-gram reduction of meat was well within the intake
variation (standard deviation) of 55 gram and is thus a
realistic scenario. Meat intake has been linked to an in-
creased risk of mortality before [29]. In addition, other
meat substitution studies reported reduced mortality [17]
or cardiovascular risks [16]. Temme et al. showed that a
complete replacement of meat and dairy by a variety of
plant-derived foods would not affect total iron intake, re-
duce saturated fatty acid intake, and reduce land use by
around 50% in Dutch female young adults [30].
Substituting high-GHGE with low-GHGE meats could
also contribute to increased survival rates and reduced
environmental impact. Replacing red meat with poultry
would reduce the environmental impact (data Blonk
Consultants ) and is associated with reduced mortality
risk [17]. In addition, processed meat intake appears to
be stronger associated with several morbidity outcomes
than red meat [31]. Replacement of meat by fish can be
considered controversial from an ecological point of
view, because of sustainability concerns of the current
ocean fishing and fish cultivation practices.
A New Zealand study presented findings of scenario
development with linear programming that determined
several dietary patterns to cover nutrient intake at low
cost and low GHGE profiles [32]. The study suggests
that these results could provide guidance to govern-
ments decisions around the focus of their food policies,
i.e. food taxes, healthy food vouchers and subsidies. An
UK study investigated the effect of incorporating the so-
cietal cost of GHGE into the price of foods [33]. A sce-
nario in which a higher taxation rate is calculated for
foods above GHGE average shows that this could save
7770 lives in the UK each year, reduce GHGE and gener-
ate tax revenue. These studies highlight the potential
benefits of such policy measures on health and environ-
ment impact of the diet.
Table 4 Data for mortality risks according to total land use of usual diet in EPIC-NL
Land use (m
2
*year/d) Pfor
linear trend
<2.99 2.99 - 3.61 3.61 –4.28 >4.28
All-cause mortality
No. of participants 8769 8771 8770 8769
No. of deaths 741 669 595 558
Person-years, median 15.8 15.9 15.8 16.0
Crude HR
a
(95% CI) 1 (REF) 0.89 (0.80-0.99) 0.79 (0.71-0.88) 0.74 (0.66-0.82) P< 0.0001
d
Model 1
b
HR 1 0.99 (0.86-1.15) 0.99 (0.85-1.14) 1.05 (0.89-1.23) P= 0.6190
Model 2
b,c
HR 1 0.99 (0.85-1.14) 0.97 (0.82-1.15) 1.03 (0.84-1.25) P= 0.8534
Cause-specific mortality
Cancer
No. of deaths 326 317 282 268
Crude HR
a
(95% CI) 1 (REF) 0.97 (0.83-1.13) 0.86 (0.73-1.01) 0.82 (0.69-0.96) P= 0.0057
d
Model 1
b
HR 1 1.05 (0.86-1.29) 0.99 (0.80-1.22) 1.10 (0.88-1.37) P= 0.5291
CVD
No. of deaths 164 151 112 118
Crude HR
a
(95% CI) 1 (REF) 0.91 (0.73-1.14) 0.68 (0.53-0.86) 0.71 (0.56-0.90) P= 0.0010
d
Model 1
b
HR 1 1.03 (0.75-1.41) 0.97 (0.68-1.37) 1.07 (0.75-1.54) P= 0.7666
Respiratory diseases
No. of deaths 44 30 34 29
Crude HR
a
(95% CI) 1 (REF) 0.68 (0.42-1.07) 0.77 (0.49-1.20) 0.65 (0.41-1.04) P= 0.1086
Model 1
b
HR 1 0.81 (0.42-1.56) 0.97 (0.49-1.90) 1.19 (0.58-2.46) P= 0.5950
Other causes
No. of deaths 162 133 122 112
Crude HR
a
(95% CI) 1 (REF) 0.81 (0.65-1.02) 0.75 (0.59-0.95) 0.68 (0.54-0.87) P= 0.0016
d
Model 1
b
HR 1 0.83 (0.60-1.16) 0.98 (0.70-1.36) 0.88 (0.61-1.27) P= 0.6518
a
HR: hazard ratio;
b
Cox stratified for age (continuous) and adjusted for sex;
c
Additional adjusted for energy intake.
d
p value for linear trend significant (p < 0.05).
Biesbroek et al. Environmental Health 2014, 13:27 Page 7 of 9
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Our study has some strengths and limitations. The
combination of sustainability of the usual diet and health
was not previously studied in a large prospective cohort
with a follow-up time of 16 years. The participants of
this cohort were sampled from four different geographic
areas in the Netherlands and therefore the results may
be extrapolated to the Dutch population. In addition,
mean GHGE and land use in our cohort were similar to
the Dutch Consumption Survey of 1998 [3]. The dietary
assessment took place only in the nineties, while now-
adays people might have different eating patterns and
eat foods that are produced differently. A FFQ is de-
signed to rank people according to their diet. Therefore,
the modelled substitution of the 35 g/d of meat was not
based on actual intake but was estimated with usual in-
take. However, our outcomes clearly demonstrate health
and environmental benefits from a dietary shift towards
lower meat consumption.
The scope of this study is limited to substitutions of an
equivalent quantity in grams. Future research may include
iso-caloric substitutions or nutritional component equiva-
lency of meat substitutions. In addition, within food
groups the environmental impact can vary per product
due to farming methods, animal feed, use of side products,
transport, and growing conditions [24]. Taking the variety
of distributions of environmental impact for every stage of
the production process would allow for variance estima-
tion of the environmental impact of a food group. This
would further improve the GHGE and land use estimates
used in our study. Other research may focus on the role of
governmental decisions on consumer behaviour and its ef-
ficacy. Examples of governmental actions could be a food-
labelling system that indicates GHGE per 100-gram prod-
uct, food taxes based on a combination of health aspects
and environmental impact of a product, or media cam-
paigns to inform consumers of environmental impact of
foods.
Conclusions
The Dutch diet is relatively high in animal-derived food
products and refined carbohydrates and low in fruit and
vegetables. Within the dietary range of this population-
based cohort, there were no significant associations be-
tween overall daily dietary-derived GHGE and land use
and mortality. However, a modelled reduction of 35 gram
meat which was replaced with vegetables, fruits, fish, or
cereal-rice-couscous resulted in lower GHGE and land use
as well as decreased all-cause mortality risk. The results of
our study emphasise that a healthier diet is not necessarily
amoresustainablediet,andtheotherwayaround.Never-
theless, a reduction of meat consumption can influence
both health and environmental aspects.
Abbreviations
BMI: Body mass index; CPAI: Cambridge physical activity index;
EPIC: European Prospective Investigation into Cancer and Nutrition;
FFQ: Food frequency questionnaire; GHGE: Greenhouse gas emission;
HR: Hazard ratio; 95% CI: 95% confidence interval.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
SB carried out the statistical analysis, prepared the tables and figures, and
wrote the paper, taking into account comments from all the co-authors.
EHMT and HBB-d-M initiated and designed this study. EHMT was the overall
project coordinator. HBB-d-M and EHMT were members of the writing group
and gave input on the statistical analysis and interpretation of the results.
HBB-d-M, PHMP, WMMV, and YTS are members of the EPIC-NL steering
committee. All authors provided comments and suggestions on the
manuscript and approved the final version.
Acknowledgments
This work was supported by the ‘Europe against Cancer’Program of the
European Commission (DG-SANCO); the Dutch Ministry of Public Health,
Welfare and Sports; the Dutch Ministry of Economic Affairs, the Dutch Cancer
Society; ZonMw (the Netherlands Organization for Health Research and
Development); and the World Cancer Research Fund (WCRF). In addition, we
thank Marjolein Geurts of the RIVM for reading and editing the manuscript.
Author details
1
Centre for Nutrition, Prevention and Health Services, The National Institute
for Public Health and the Environment (RIVM), Antonie van Leeuwenhoek 9,
Bilthoven 3721 MA, The Netherlands.
2
Department of Gastroenterology and
Hepatology, University Medical Centre Utrecht, Heidelberglaan 100, 3508 GA
Utrecht, The Netherlands.
3
School of Public Health, Imperial College London,
London SW7 2AZ, United Kingdom.
4
Julius Centre, University Medical Centre
Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands.
5
Blonk
Consultants, Gravin Beatrixstraat 34, 2805 PJ Gouda, The Netherlands.
6
School
of Business and Administration Sao Paolo, Av. Nove de Julho 2029
01313-902, São Paulo, Brasil.
Received: 18 December 2013 Accepted: 2 April 2014
Published: 7 April 2014
Table 5 Environmental impact of 35 gram modelled meat
substitution by predefined food groups and all-cause
mortality
Substitute Reduction
GHGE (%)
a
Reduction land
use (%)
a
Reduction
mortality risk
(%, 95% CI)
b
Potatoes 10.8 11.3 0 (−6–7)
Pasta-rice-
couscous
10.1 9.7 11 (4 –16)
Vegetables 10.0 10.8 9 (3 –15)
Fruit, nuts and seeds 10.0 10.3 6 (1 –10)
Milk-based desserts
c
10.0 10.9 4 (0 –9)
Fish 4.5 9.8 19 (3 –33)
Cheese 0.6 4.5 6 (−4–14)
Remove 35 gram meat 11.5 11.7 4 (2 –7)
(No replacement)
a
Based on the average greenhouse gas emission (GHGE) and land use in EPIC-NL;
b
Cox stratified for age (continuous) and adjusted for gender, BMI (continuous),
smoking status, physical activity, energy intake (continuous), and alcohol intake
(continuous); c: consists of (fruit)yoghurt, cream desserts, and milk-based puddings.
Biesbroek et al. Environmental Health 2014, 13:27 Page 8 of 9
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References
1. Lang T, Barling D: Nutrition and sustainability: an emerging food policy
discourse. Proc Nutr Soc 2013, 72:1–12.
2. Tukker A, Huppes G, Guinée J, Heijungs R, Koning A, Oers L, Suh S, Geerken
T, Holderbeke M, Jansen B: Environmental Impact of Products (EIPRO) Analysis
of the life cycle environmental impacts related to the final consumption of the
EU-25. Brussels: European Commision, Joint Research Centre, Institure for
Prospective Technological Studies; 2006.
3. Marinussen M, Kramer G, Pluimers J, Blonk H: The environmental impact of
our diet - an analysis based on de nutitional consumption survey of
2007–2010 (in Dutch, summary in English). In Book The environmental
impact of our diet - an analysis based on de nutitional consumption survey of
2007–2010 (in Dutch, summary in English). Gouda: Blonk Milieu Advies; 2012.
4. Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Pretty
J, Robinson S, Thomas SM, Toulmin C: Food security: the challenge of
feeding 9 billion people. Science 2010, 327:812–818.
5. Westhoek H, Rood T, Van den Berg M, Janse J, Nijdam D, Reudink M,
Stehfest E: The protein puzzle. The Hague: PBL Netherlands Environmental
Assessment Agency; 2011:221.
6. Lock K, Pomerleau J, Causer L, Altmann DR, McKee M: The global burden of
disease attributable to low consumption of fruit and vegetables: implications
for the global strategy on diet. Bull World Health Organ 2005, 83:100–108.
7. Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A: Meat intake and
mortality: a prospective study of over half a million people. Arch Intern
Med 2009, 169:562–571.
8. Cordain L, Eaton SB, Sebastian A, Mann N, Lindeberg S, Watkins BA, O’Keefe JH,
Brand-Miller J: Origins and evolution of the Western diet: health implications
for the 21st century. Am J Clin Nutr 2005, 81:341–354.
9. Pimentel D, Pimentel M: Sustainability of meat-based and plant-based
diets and the environment. Am J Clin Nutr 2003, 78:660S–663S.
10. Health Council of the Netherlands: Guidelines for a healthy diet 2006. The
Hague: Health Council of the Netherlands; 2006. publciation no. 2006/21.
11. Scarborough P, Allender S, Clarke D, Wickramasinghe K, Rayner M:
Modelling the health impact of environmentally sustainable dietary
scenarios in the UK. Eur J Clin Nutr 2012, 66(6):710–715.
12. Hoolohan C, Berners-Lee M, McKinstry-West J, Hewitt C: Mitigating the
greenhouse gas emissions embodied in food through realistic consumer
choices. Energy Policy 2013, 63:1065–1074.
13. Vieux F, Darmon N, Touazi D, Soler L: Greenhouse gas emissions of
self-selected individual diets in France: Changing the diet structure or
consuming less? Ecol Econ 2012, 75:91–101.
14. Stehfest E, Bouwman L, van Vuuren DP, den Elzen MGJ, Eickhout B, Kabat P:
Climate benefits of changing diet. Clim Chang 2009, 95:83–102.
15. Macdiarmid JI, Kyle J, Horgan GW, Loe J, Fyfe C, Johnstone A, McNeill G:
Sustainable diets for the future: can we contribute to reducing
greenhouse gas emissions by eating a healthy diet? Am J Clin Nutr 2012,
96:632–639.
16. Bernstein AM, Sun Q, Hu FB, Stampfer MJ, Manson JE, Willett WC: Major
dietary protein sources and risk of coronary heart disease in women.
Circulation 2010, 122:876–883.
17. Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Stampfer MJ, Willett WC,
Hu FB: Red meat consumption and mortality: results from 2 prospective
cohort studies. Arch Intern Med 2012, 172:555.
18. Beulens JWJ, Monninkhof EM, Verschuren WMM, van der Schouw YT, Smit J,
Ocke MC, Jansen EHJM, van Dieren S, Grobbee DE, Peeters PHM: Cohort
profile: the EPIC-NL study. Int J Epidemiol 2010, 39:1170–1178.
19. Boker LK, Van Noord P, Van Der Schouw Y, Koot N, de Mesquita HBB, Riboli E,
Grobbee D, Peeters P: Prospect-EPIC Utrecht: study design and
characteristics of the cohort population. Eur J Epidemiol 2001, 17:1047–1053.
20. Verschuren W, Blokstra A, Picavet H, Smit H: Cohort profile: the
Doetinchem cohort study. Int J Epidemiol 2008, 37:1236–1241.
21. Blokstra A, Smit H, Bueno de Mesquita H, Seidell J, Verschuren W:
Monitoring of risk factors and health in the Netherlands (MORGEN-cohort)
1993–1997. Lifestyle- and risk factors: prevalences and trends (in Dutch).
Bilthoven: RIVM; 2005.
22. Ocke MC, Bueno-de-Mesquita HB, Goddijn HE, Jansen A, Pols MA,
van Staveren WA, Kromhout D: The Dutch EPIC food frequency
questionnaire. I. Description of the questionnaire, and relative validity
and reproducibility for food groups. Int J Epidemiol 1997, 26:S37.
23. Ocke MC, Bueno-de-Mesquita HB, Pols MA, Smit HA, van Staveren WA,
Kromhout D: The Dutch EPIC food frequency questionnaire. II Relative
validity and reproducibility for nutrients International. J Epidemiol 1997,
26:S49.
24. Garnett T: Cooking up a storm: Food, greenhouse gas emissions and our
changing climate. In Book Cooking up a storm: Food, greenhouse gas
emissions and our changing climate. Food Climate Research Network, Centre
for Environmental Strategy, University of Surrey; 2008.
25. IPCC: Climate change 2007: The physical science basis. Geneva: Cambrigde
University Press; 2007.
26. Pols MA, Peeters P, Ocke MC, Slimani N, Bueno-de-Mesquita HB, Collette H:
Estimation of reproducibility and relative validity of the questions
included in the EPIC Physical Activity Questionnaire. Int J Epidemiol 1997,
26:S181.
27. Petrie A, Sabin C: Medical statistics at a glance. Oxford: Blackwell Pub; 2009.
28. Macdiarmid J: Is a healthy diet an enviromental sustainable diet? Proc
Nutr Soc 2013, 72:13–20.
29. Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R,
Tjønneland A, Nailler L, Boutron-Ruault M-C, Clavel-Chapelon F, Krogh V:
Meat consumption and mortality-results from the European Prospective
Investigation into Cancer and Nutrition. BMC Med 2013, 11:63.
30. Temme E, van der Voet H, Thissen J, Verkaik-Kloosterman J, van Donkersgoed G,
Nonhebel S: Replacement of meat and dairy by plant-derived foods:
estimatedeffectsonlanduse,ironandSFAintakesinyoungDutchadult
females. Public Health Nutr 2013, 16(10):1900–1907.
31. Micha R, Wallace SK, Mozaffarian D: Red and processed meat consumption
and risk of incident coronary heart disease, stroke, and diabetes mellitus
a systematic review and meta-analysis. Circulation 2010, 121:2271–2283.
32. Wilson N, Nghiem N, Mhurchu CN, Eyles H, Baker MG, Blakely T: Foods and
dietary patterns that are healthy, low-cost, and environmentally
sustainable: a case study of optimization modeling for New Zealand.
PLoS One 2013, 121(21):2271–2283.
33. Briggs AD, Kehlbacher A, Tiffin R, Garnett T, Rayner M, Scarborough P: Assessing
the impact on chronic disease of incorporating the societal cost of
greenhouse gases into the price of food: an econometric and comparative
risk assessment modelling study. BMJ Open 2013, 3(10):e003543.
doi:10.1186/1476-069X-13-27
Cite this article as: Biesbroek et al.:Reducing our environmental
footprint and improving our health: greenhouse gas emission and land
use of usual diet and mortality in EPIC-NL: a prospective cohort study.
Environmental Health 2014 13:27.
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