Literature Review

Are Organic Foods Safer or Healthier Than Conventional Alternatives?

Article· Literature Review (PDF Available)inAnnals of internal medicine 157(5):348-66 · September 2012with 7,543 Reads 
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DOI: 10.7326/0003-4819-157-5-201209040-00007 · Source: PubMed
Cite this publication
Abstract
The health benefits of organic foods are unclear. To review evidence comparing the health effects of organic and conventional foods. MEDLINE (January 1966 to May 2011), EMBASE, CAB Direct, Agricola, TOXNET, Cochrane Library (January 1966 to May 2009), and bibliographies of retrieved articles. English-language reports of comparisons of organically and conventionally grown food or of populations consuming these foods. 2 independent investigators extracted data on methods, health outcomes, and nutrient and contaminant levels. 17 studies in humans and 223 studies of nutrient and contaminant levels in foods met inclusion criteria. Only 3 of the human studies examined clinical outcomes, finding no significant differences between populations by food type for allergic outcomes (eczema, wheeze, atopic sensitization) or symptomatic Campylobacter infection. Two studies reported significantly lower urinary pesticide levels among children consuming organic versus conventional diets, but studies of biomarker and nutrient levels in serum, urine, breast milk, and semen in adults did not identify clinically meaningful differences. All estimates of differences in nutrient and contaminant levels in foods were highly heterogeneous except for the estimate for phosphorus; phosphorus levels were significantly higher than in conventional produce, although this difference is not clinically significant. The risk for contamination with detectable pesticide residues was lower among organic than conventional produce (risk difference, 30% [CI, -37% to -23%]), but differences in risk for exceeding maximum allowed limits were small. Escherichia coli contamination risk did not differ between organic and conventional produce. Bacterial contamination of retail chicken and pork was common but unrelated to farming method. However, the risk for isolating bacteria resistant to 3 or more antibiotics was higher in conventional than in organic chicken and pork (risk difference, 33% [CI, 21% to 45%]). Studies were heterogeneous and limited in number, and publication bias may be present. The published literature lacks strong evidence that organic foods are significantly more nutritious than conventional foods. Consumption of organic foods may reduce exposure to pesticide residues and antibiotic-resistant bacteria. None.
Are Organic Foods Safer or Healthier Than Conventional Alternatives?
A Systematic Review
Crystal Smith-Spangler, MD, MS; Margaret L. Brandeau, PhD; Grace E. Hunter, BA; J. Clay Bavinger, BA; Maren Pearson, BS;
Paul J. Eschbach; Vandana Sundaram, MPH; Hau Liu, MD, MS, MBA, MPH; Patricia Schirmer, MD; Christopher Stave, MLS;
Ingram Olkin, PhD; and Dena M. Bravata, MD, MS
Background: The health benefits of organic foods are unclear.
Purpose: To review evidence comparing the health effects of or-
ganic and conventional foods.
Data Sources: MEDLINE (January 1966 to May 2011), EMBASE,
CAB Direct, Agricola, TOXNET, Cochrane Library (January 1966 to
May 2009), and bibliographies of retrieved articles.
Study Selection: English-language reports of comparisons of or-
ganically and conventionally grown food or of populations consum-
ing these foods.
Data Extraction: 2 independent investigators extracted data on
methods, health outcomes, and nutrient and contaminant levels.
Data Synthesis: 17 studies in humans and 223 studies of nutrient
and contaminant levels in foods met inclusion criteria. Only 3 of the
human studies examined clinical outcomes, finding no significant
differences between populations by food type for allergic outcomes
(eczema, wheeze, atopic sensitization) or symptomatic Campylo-
bacter infection. Two studies reported significantly lower urinary
pesticide levels among children consuming organic versus conven-
tional diets, but studies of biomarker and nutrient levels in serum,
urine, breast milk, and semen in adults did not identify clinically
meaningful differences. All estimates of differences in nutrient and
contaminant levels in foods were highly heterogeneous except for
the estimate for phosphorus; phosphorus levels were significantly
higher than in conventional produce, although this difference is not
clinically significant. The risk for contamination with detectable pes-
ticide residues was lower among organic than conventional produce
(risk difference, 30% [CI, 37% to 23%]), but differences in risk
for exceeding maximum allowed limits were small. Escherichia coli
contamination risk did not differ between organic and conventional
produce. Bacterial contamination of retail chicken and pork was
common but unrelated to farming method. However, the risk for
isolating bacteria resistant to 3 or more antibiotics was higher in
conventional than in organic chicken and pork (risk difference, 33%
[CI, 21% to 45%]).
Limitation: Studies were heterogeneous and limited in number,
and publication bias may be present.
Conclusion: The published literature lacks strong evidence that
organic foods are significantly more nutritious than conventional
foods. Consumption of organic foods may reduce exposure to
pesticide residues and antibiotic-resistant bacteria.
Primary Funding Source: None.
Ann Intern Med. 2012;157:348-366. www.annals.org
For author affiliations, see end of text.
Between 1997 and 2010, U.S. sales of organic foods
increased from $3.6 to $26.7 billion (1, 2). Although
prices vary, consumers can pay up to twice as much for
organic than conventional foods (3–5).
Organic certification requirements and farming prac-
tices vary worldwide, but organic foods are generally grown
without synthetic pesticides or fertilizers or routine use of
antibiotics or growth hormones (6, 7). Organic livestock
are fed organically produced feed that is free of pesticides
and animal byproducts and are provided access to the out-
doors, direct sunlight, fresh air, and freedom of movement
(7). In addition, organic regulations typically require that
organic foods are processed without irradiation or chemical
food additives and are not grown from genetically modified
organisms (6, 8). The International Federation of Organic
Agriculture Movements endorses the principles of “health,
ecology, fairness, and care” (9).
Consumers purchase organic foods for different rea-
sons, including concerns about the effects of conventional
farming practices on the environment, human health, and
animal welfare and perceptions that organic foods are tast-
ier than their conventional alternatives (2, 10–13).
The purpose of this study is to comprehensively syn-
thesize the published literature on the health, nutritional,
and safety characteristics of organic and conventional
foods. Previous reviews comparing the nutritional content
of organic and conventional foods have summarized stud-
ies narratively (13–18), reported differences in nutrient lev-
els without assessing the statistical significance of those dif-
ferences or weighting outcomes by sample size (19–22), or
considered only harms (23).
METHODS
Data Sources and Searches
With a professional librarian, we developed search
strategies for 7 databases: MEDLINE (January 1966 to
May 2011), EMBASE, CAB Direct, Agricola, TOXNET,
and Cochrane Library (January 1966 to May 2009) with
such terms as organic,vegetable,fruit, and beef (Supple-
See also:
Web-Only
Supplements
Annals of Internal MedicineReview
348 © 2012 American College of Physicians
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ment 1, available at www.annals.org) and reviewed bibli-
ographies of retrieved articles.
Study Selection
Peer-reviewed, English-language studies, regardless of
design, were eligible for inclusion if they reported a com-
parative evaluation of populations consuming diets of
foods grown organically and conventionally or a compara-
tive evaluation of nutrient levels or bacterial, fungal, or
pesticide contamination of fruits, vegetables, grains, meats,
poultry, milk (including raw milk), or eggs grown organi-
cally and conventionally. We excluded studies of processed
foods, those that evaluated samples from livestock feces or
gastrointestinal tracts, and those that did not report infor-
mation about variance or results of statistical tests (24–34).
Organic practices included biodynamic farming and were
defined by investigators’ stated adherence. Studies merely
comparing the effects of organic and nonorganic fertiliza-
tion practices were ineligible unless they specified that the
produce receiving organic fertilizer was grown by using
organic farming practices (28, 32, 33, 35–47). Similarly,
we excluded studies of such foods as recombinant bovine
somatotropin–free milk and grass-fed beef unless the food
production was reported to be organic.
Data Extraction and Quality Assessment
One author abstracted data on study methods (for ex-
ample, design; food tested; sample size; organic standard;
testing methods; harvest season; and cultivar, breed, or
population studied) and end points (Supplement 2, avail-
able at www.annals.org). At least 1 additional author veri-
fied all abstracted data; discrepancies were resolved with
discussion. If 2 or more studies presented the same data
from a single population or the same farm experiment, we
included these data only once in our analyses.
We defined quality criteria a priori and evaluated the
extent to which included human population studies speci-
fied the organic standard used, evaluated the amount of
organic foods consumed in diets, linked reported outcomes
with health outcomes, obtained institutional review board
approval and participant consent, and were not funded by
an organization with a financial interest in the study out-
come. For the studies that directly evaluated the study
foods, we evaluated the extent to which each study speci-
fied the organic standard used, used the same harvesting or
processing method for both groups, reported sample size,
used equal sample size in both groups, and were not
funded by organizations with a financial interest in the
study outcome. We also evaluated the extent to which the
organic–conventional comparison pairs were of the same
cultivar or breed, grown on neighboring farms, and har-
vested during the same season.
Data Synthesis and Analysis
We calculated summary effect sizes by using random-
effects models for outcomes with at least 3 studies report-
ing data: summary risk differences (RDs) and summary
prevalence rates for studies reporting the number of sam-
ples contaminated and summary standardized mean differ-
ences (SMDs) for studies reporting mean nutrient or harm
levels. Differences were calculated as organic minus con-
ventional (for example, a positive number indicates more
contamination in organic). All RDs are absolute RDs.
We performed tests of homogeneity (Qstatistic and I
2
statistic) on all summary effect sizes. Homogeneity was
indicated if I
2
was less than 25% and Pvalue for the Q
statistic was greater than 0.010. If the 2 tests agreed, we
report only the I
2
statistic; otherwise, we report results for
both. We used funnel plots to assess publication bias (48).
We qualitatively summarized studies not reporting infor-
mation on variance and excluded studies not reporting any
information on variance or statistical testing. All analyses
were completed by using Comprehensive Meta-analysis,
version 2 (Biostat, Englewood, New Jersey). Because of the
large number of comparisons (22 for produce and 31 for
meat, poultry, milk, and eggs), we report adjusted Pvalues
for summary estimates using the Sidak formula for multi-
ple comparisons. For each reported summary effect size, we
omitted 1 study at a time to assess the influence of each
individual study on summary effects and omitted outliers
that were more than 1 order of magnitude larger or smaller
than others. We explored heterogeneity by conducting sub-
group analyses by food type, organic standard used, testing
method, and study design when at least 3 studies examined
these subgroups.
We limited our analyses of bacterial contamination to
foodborne pathogens monitored by the Centers for Disease
Control and Prevention’s FoodNet (49) (for example,
Campylobacter,Listeria,Salmonella, and Escherichia coli).
However, given the potential for transfer of antibiotic re-
sistance between species, we included all human pathogens
(for example, Staphylococcus aureus) in the analyses of anti-
biotic resistance.
Studies frequently reported several results per outcome
(for example, mean vitamin C level in years 1 and 2). To
include such studies only once in our analyses, we com-
bined the results within each study by using random-effects
models and used this study-level summary effect in our
overall summary calculation.
Similarly, several studies (50–53) reported multiple re-
sults for resistance to the same antibiotic by examining
different bacteria (for example, Salmonella and Campylo-
bacter). To include these studies only once in each effect
size calculation, we used results for pathogens in the Entero-
bacteriaceae family (for example, Salmonella) for the main
analyses and the alternate species (for example, Campylo-
bacter) in sensitivity analysis.
Among the produce studies, several studies that other-
wise could have been included in summary effect size cal-
culations did not report sample sizes. To avoid discarding
them, we assumed that they had a sample size of 3 (a
common sample size among the smaller studies). In sensi-
tivity analyses, we varied this to 10, the median sample size
among studies. This alternate assumption did not change
ReviewOrganic Versus Conventional Foods
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conclusions, so we report the outcomes using a sample size
of 3.
Role of the Funding Source
This study did not receive external funding.
RESULTS
Searches identified 5908 potentially relevant articles
(Appendix Figure 1, available at www.annals.org). Two
hundred thirty-seven studies met inclusion criteria: 17
evaluated health outcomes among human populations con-
suming organic and conventional foods (54–70); 223
compared organic and conventional fruits, vegetables,
grains, meats, poultry, milk, or eggs directly (50–53, 57,
65, 69, 71–286) (3 reported on both human and food
outcomes). Supplement 2 lists all studies reporting each
outcome and studies included in each subgroup analysis.
Studies in Humans Consuming Organic and
Conventional Foods
Seventeen articles describing 14 unique populations
(13 806 participants) met inclusion criteria (Supplement
3, available at www.annals.org). Study designs varied: 6
randomized, controlled trials (56, 57, 62, 65, 66, 69), 2
prospective cohort studies (54, 61), 3 cross-sectional stud-
ies (55, 64, 68), 4 crossover studies (describing 2 popula-
tions) (59, 60, 63, 67), and 1 case–control study (70).
Only 3 studies (61, 64, 70) examined clinical outcomes
(for example, wheezing, allergic symptoms, or reported
Campylobacter infections), and the remaining studies exam-
ined health markers (for example, serum lipid or vitamin
levels).
In general, the included studies were of fair quality
(Appendix Figure 2 [top panel], available at www.annals
.org). Only 6 studies specified the organic standard used.
Only 5 studies (54, 61, 64, 65, 68) evaluated participants
who consumed a predominately organic diet; participants
in the remaining studies consumed only certain organic
foods (for example, apples [62], carrots [69], or meat or
dairy products [68]). The sample sizes ranged from 6 to
6630, and duration ranged from 2 days to 2 years. Four
studies were from the United States (55, 59, 60, 63), and
all others were from Europe.
Studies in Pregnant Women and Children
One prospective cohort study (61) and 1 cross-
sectional study (64) of pregnant women and their children
reported no association between diet type and the develop-
ment of eczema, wheezing, serum IgE levels, or other
atopic outcomes among children. Exploratory subgroup
analyses found that children who consumed dairy products
of which more than 90% were organically produced had a
lower risk for eczema at age 2 years than children who
consumed dairy products of which less than 50% were
organically produced (odds ratio, 0.64 [95% CI, 0.44 to
0.93]) (61).
Three other studies examined markers of pesticide or
insecticide exposure in children. One cross-sectional study
(55) and 1 crossover study (59) examined urinary organo-
phosphate pesticide metabolites, finding significantly lower
levels among children on organic diets than those on con-
ventional diets. Although these studies suggest that con-
sumption of organic fruits and vegetables may significantly
reduce pesticide exposure in children, they were not de-
signed to assess the link between the observed urinary pes-
ticide levels and clinical harm. One crossover study com-
paring urinary insecticide levels among children spending 5
days on a conventional diet followed by 5 days on an
organic diet found household use of insecticides—but not
diet—to be a significant predictor of urinary insecticide
levels (60).
Studies in Nonpregnant Adults
Eleven reports of 10 populations examined differences
between adults consuming organic and conventional diets.
Only 1 reported clinical outcomes: An exploratory case–
control study (70) found consumption of organic meat in
Figure 1. Organic standards used for studies of produce and
animal products.
USDA
EEC
Other European country
regulatory standard
Regulatory standard
non–European Union,
non–United States
IFOAM
Other organic
association standards
Studies Using Standard, n
Produce
0
60
50
40
30
20
10
70
Animal Products
Sixty-five produce studies and 37 studies of animal products reported the
organic standard applied. EEC European Economic Community;
IFOAM International Federation of Organic Agriculture Movements;
USDA U.S. Department of Agriculture.
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the winter (but not organic meat in general) to be a risk
factor for illness due to Campylobacter infection (odds ra-
tio, 6.86 [CI, 1.49 to 31.69]).
The remaining studies examined differences in the se-
rum, urine, breast milk, and semen of persons consuming
organic and conventional diets. We found no studies com-
paring pesticide levels among adult consumers of organic
versus conventional foods.Seven studies evaluated serum
and urine antioxidant levels or immune system markers; 6
of these found no consistent differences in plasma or urine
carotenoids, polyphenols, vitamins E and C content, low-
density lipoprotein cholesterol, antioxidant activity, ability
to protect against DNA damage, immune system markers,
or semen quality between participants consuming organic
and conventional diets (54, 57, 62, 65, 66, 69). All were
randomized, controlled trials except the study of semen
quality (a prospective cohort study) (54). One prospective
crossover study reported a statistically significant reduction
in serum total homocysteine levels, phosphorus levels, and
fat mass after 2 weeks on an organic Mediterranean diet
compared with a conventional Mediterranean diet but did
not describe the magnitude or clinical significance of these
reductions (67). Another crossover study found that or-
ganic diets were associated with higher urinary excretion of
quercetin and kaempferol but not other polyphenols and
found no difference in 7 of 8 serum markers of antioxida-
tion (56).
Two cross-sectional studies examined the breast milk
of women from the Dutch KOALA (Child, Parent, and
Health: Lifestyle and Genetic Constitution) Birth Cohort
consuming predominantly organic versus conventional
meat and dairy products (58, 68). They found no differ-
ence in the amount of total fatty acids in the breast milk of
mothers who consumed meat and dairy products of which
Table 1. Summary of Benefits: SMD of Nutrient Levels Found in Organic Versus Conventional Fruits, Vegetables, and Grains*
Nutrient Summary of All Identified Studies Results of Meta-analysis
Studies,
n
Comparisons,
n
Comparisons
Favor
Organic,
n
Comparisons
Favor
Conventional,
n
Studies,
n
§
Studies
Describing
Sample
Size,
n
Organic
Sample
Size,
n
Conventional
Sample Size,
n
SMD (95% CI)P
Value¶
Heterogeneous
(
I
2
Statistic)
Ascorbic acid Foods studied: banana, berries, broccoli, cabbage, carrots, celery, eggplant, grapes, leafy greens, lettuce, oranges, peaches, pears, peppers, plums, potatoes,
strawberries, and tomatoes
41 113 23 12 31 28 1141 1306 0.50 (0.05 to 0.95) 0.48 Yes (80%)
-Carotene Foods studied: eggplant, plums, carrots, tomatoes, sweet peppers, kale, and orange
16 23 6 3 12 6 114 114 1.14 (0.13 to 2.42) 0.83 Yes (91%)
-Tocopherol Foods studied: peaches, pears, plums, corn, cabbage, carrots, and olive oil
819 3 2 55 6060 0.09 (0.70 to 0.53) 1.00 Yes (26%)
Potassium Foods studied: carrots, celery, corn, oranges, grapes, potatoes, peppers, plums, onions, strawberries, and wheat
37 108 18 18 14 9 300 315 0.45 (0.30 to 1.20) 1.00 Yes (87%)
Calcium Foods studied: carrots, celery, corn, oranges, peppers, plums, strawberries, onions, potatoes, and wheat
36 105 18 7 15 11 484 500 0.61 (0.01 to 1.22) 0.68 Yes (84%)
Phosphorus Foods studied: carrots, celery, corn, plums, onions, and potatoes
30 82 24 12 7 6 353 374 0.82 (0.44 to 1.20) 0.001 No (0%)
Magnesium Foods studied: potato, plums, onions, peas, carrots, celery, corn, cabbage, strawberries, peppers, tomato, orange, and wheat
34 86 23 6 13 10 352 362 0.65 (0.01 to 1.30) 0.66 Yes (81%)
Iron Foods studied: potato, plums, onions, peas, corn, cabbage, carrots, strawberries, peppers, wheat, oats, and tomatoes
24 77 10 12 12 9 350 300 0.30 (0.47 to 1.08) 1.00 Yes (90%)
Protein Foods studied: wheat, banana, plum, tomato, soybeans, grape juice, and eggplant
27 63 7 34 14 8 93 108 1.27 (3.20 to 0.62) 1.00 Yes (83%)
Fiber Foods studied: banana, eggplant, plums, wheat, grape juice, and oranges
811 2 5 73 7390 0.79 (1.87 to 0.29) 0.97 Yes (83%)
Quercetin Foods studied: plums, tomatoes, bell peppers, grapes, grape leaves, lettuce, strawberries, and black currants
13 50 16 2 11 6 156 156 2.45 (0.20 to 4.69) 0.52 Yes (94%)
Kaempferol Foods studied: plums, black currants, grapes, lettuce, bok choi, collard greens, tomatoes, bell peppers, strawberries, and tomatoes
9 18 6 2 9 5 96 96 2.64 (0.41 to 4.86) 0.36 Yes (93%)
Total
flavanoids
Foods studied: apples, grape leaves, strawberries, chicory, and black currants
522 7 6 53 9696 0.19 (1.68 to 1.31) 1.00 Yes (59%)
Total phenols Foods studied: apples, peaches, pears, plums, bell peppers, berries, tomatoes, chicory, olive oil, grape leaves, oranges, strawberries, bok choi, lettuce, leafy
greens, tomatoes, and wheat
34 102 36 12 22 19 401 401 1.03 (0.47 to 1.59) 0.007 Yes (67%)
SMD standardized mean difference.
*All summary effect measures reported are results of random-effects models. Among studies examining nutritional content, studies with null findings tended to report results
incompletely (hence, they were excluded from syntheses). The exception to this rule was among studies reporting on protein content of organic vs. conventional grain: Studies
insufficiently reporting results (hence, they were excluded from summary effect calculation) tended to find significantly higher levels of protein in conventional vs. organic
grains. In calculation of summary effect sizes, sensitivity analyses were performed, in which studies not reporting sample size were removed, and subgroup analyses were done
by fresh vs. dry weight. Findings did not substantially change with the sensitivity analyses.
The number of comparisons in which a statistically significant difference was identified with higher levels in the organic group.
The number of comparisons with a statistically significant difference with higher levels in the conventional group.
§Supplement 2 (available at www.annals.org) lists the studies included for each statistical analysis.
The difference between mean nutrient level in organic minus that in conventional divided by the pooled SD; thus, a positive (negative) number indicates higher (lower)
nutrient levels in organic.
All summary Pvalues are adjusted Pvalues.
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more than 90% were organically produced versus mothers
who consumed meat and dairy products of which less than
50% were organically produced (58, 68). In subanalyses,
they found higher levels of 2 beneficial fatty acids (conju-
gated linoleic acid and trans-vaccenic acid) in the breast
milk of mothers consuming predominantly organic dairy
and meat products versus mothers consuming conventional
alternatives (58).
Studies of Nutrient and Contaminant Levels in Organic
Versus Conventional Foods
Two hundred twenty-three studies of foods met inclu-
sion criteria: 153 studies of fruits, vegetables, and grains
and 71 studies of meats, poultry, milk, and eggs (1 study
reported on both types of foods [189]) (Supplement 4,
available at www.annals.org). Seventy percent (157 studies)
were from Europe, and 21% (47 studies) were from the
United States or Canada. Study methods varied: Among
produce studies, 52% (80 studies) were on experimental
farms in which potential confounders (for example,
weather, geography, or plant cultivar) of the relationship
between method of cultivation and nutrient levels were
controlled and 29% (44 studies) sampled food grown on
commercial farms. Among animal product studies, 11% (8
studies) were conducted on experimental farms and 56%
(40 studies) surveyed farms. Of the 37 milk studies in-
cluded, 7 examined pasteurized milk and 30 examined raw
milk (Supplement 4).
Forty-six percent (102 studies) of included studies
specified the organic cultivation standard used (Appendix
Figure 2 [bottom panel]). The most common standards
were European Union or other European country-specific
standards (43 studies), International Federation of Organic
Agriculture Movements or other association standards (34
studies), and U.S. Department of Agriculture standards
(22 studies). The most common standards among produce
studies were from organic associations; country-specific
European regulatory standards were most common among
animal product studies (Figure 1).
Sixty-eight percent (151 studies) reported that harvest-
ing or processing methods were the same for both groups;
the remaining studies largely did not describe harvesting or
processing methods (such as in studies that examined retail
Table 2. Summary of Harms: RD or SMD in Harms in Organic Versus Conventional Fruits, Vegetables, and Grains*
Harm Summary of All Identified Studies
Studies,
n
Comparisons,
n
Comparisons Favor
Organic,
n
Comparisons Favor
Conventional,
n
Any detectable pesticide residue
contamination** 22 NA
E. coli contamination
5NA
DON contamination
9NA
OTA contamination
7NA
Cadmium level
15 77 21 1
Lead level
11 49 9 7
Mercury level
334 0 0
Arsenic level
216 0 0
DON level
10 29 9 0
OTA level
415 3 2
E. coli Escherichia coli; DON deoxynivalenol; NA not applicable; OTA ochratoxin A; RD risk difference; SMD standardized mean difference.
*All summary effect measures reported are results of random-effects models.
The number of comparisons in which a statistically significant difference between organic and conventional was identified with lower levels in the organic group.
The number of comparisons with a statistically significant difference with lower levels in the conventional group.
§Supplement 2 (available at www.annals.org) lists the studies included for each statistical analysis.
RD is calculated as the risk for contamination in the organic group minus that in the conventional group; thus, a positive (negative) number indicates more (less)
contamination in organic. All RDs are absolute RDs. SMD is the difference between mean contaminant level in organic minus that in conventional divided by the pooled
SD; thus, a positive (negative) number indicates more (less) contamination in organic.
All summary Pvalues are adjusted Pvalues.
** One of the studies included in the pesticide synthesis includes a data set (U.S. Department of Agriculture’s Pesticide Data Program) that oversamples products from
sources with a history of violations. Hence, prevalence estimates may overstate prevalence of pesticide contamination in both organic and conventional products.
†† Result not robust to removal of 1 study at a time. Removal of 1 study (225) rendered results significant, suggesting higher contamination among organic produce (RD,
5.1% [95% CI, 2.92% to 7.18%]; P0.001; I
2
0%).
‡‡ For cadmium, lead, mercury, arsenic, DON, and OTA levels, these are the sample sizes instead of the number of contaminated samples divided by the total number of
samples.
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samples). Eighty-seven percent (194 studies) reported sam-
ple size; however, definitions of a sample varied (for exam-
ple, 1 sample is 10 apples from 1 tree vs. 10 apples from 1
row of trees). Sixty-five percent (146 studies) had equal
sample sizes in both groups, and 91% (204 studies) were
not funded by an organization with an overt interest in the
outcome. Eighty-six percent (61 studies) of animal product
studies sampled animal products from the same season.
Among produce studies, 59% (90 studies) and 65% (100
studies) compared food pairs from neighboring farms or
the same cultivar, respectively.
Vitamin and Nutrient Levels by Food Origin
Vitamins
We did not find significant differences in the vitamin
content of organic and conventional plant or animal prod-
ucts (Supplement 5 [available at www.annals.org] and
Table 1). Produce studies reported on ascorbic acid (31
studies),
-carotene (12 studies), and
-tocopherol (5
studies) content; milk studies reported on
-carotene (4
studies) and
-tocopherol levels (4 studies). Differences
were heterogeneous and not significant. Few studies exam-
ined vitamin content in meats, but these found no differ-
ence in
-carotene in beef (272),
-tocopherol in pork
(149) or beef (272), or vitamin A (retinol) in beef (272).
Nutrients
Summary SMDs were calculated for 11 other nutri-
ents reported in studies of produce (Table 1). Only 2 nu-
trients were significantly higher in organic than conven-
tional produce: phosphorus (SMD, 0.82 [CI, 0.44 to
1.20]; P0.001; 7 studies; median difference, 0.15
mg/kg [minimum difference, 18 mg/kg; maximum dif-
ference, 530 mg/kg]) and total phenols (SMD, 1.03 [CI,
0.47 to 1.59]; P0.007; 22 studies; median difference,
31.6 mg/kg [minimum difference, 1700 mg/kg; maxi-
mum difference, 10 480 mg/kg]). The result for phospho-
rus was homogenous (I
2
0%), but removal of 1 study
(227) reduced the summary effect size and rendered the
effect size statistically insignificant (SMD, 0.63; P
0.064). The finding for total phenols was heterogeneous
(I
2
67%) and became statistically insignificant when
studies not reporting sample size (95, 175) were removed
(P0.064). Too few studies of animal products reported
on other nutrients for effect sizes to be calculated.
Few studies examined fatty acids in milk (Supplement
6, available at www.annals.org). These studies suggest that
organic milk may contain significantly more beneficial
-3
fatty acids (SMD, 11.17 [CI, 5.93 to 16.41]; P0.001;
I
2
98%; 5 studies; median difference, 0.5 g/100 g [min-
imum difference, 0.23 g/100 g; maximum difference, 4.5
g/100 g]) and vaccenic acid than conventional milk (SMD,
2.62 [CI, 1.04 to 4.19]; P0.031; I
2
97%; 5 studies;
median difference, 0.26 g/100 g [minimum difference,
0.11 g/100 g; maximum difference, 3.1 g/100 g]). All but
1 of these studies (212) tested raw milk samples. Results
were robust to removal of 1 study at a time. Similarly,
organic chicken contained higher levels of
-3 fatty acids
than conventional chicken (SMD, 5.48 [CI, 2.19 to 8.76];
P0.031; I
2
90%; 3 studies; median difference, 1.99
g/100 g [minimum difference, 0.94 g/100 g; maximum
difference, 17.9 g/100 g]). The differences between the
remaining fatty acids examined in chicken and milk (Sup-
Table 2—Continued
Results of Meta-analysis
Studies,
n
§
Studies Describing
Sample Size,
n
Contaminated/Total
Organic,
n/N
Contaminated/Total
Conventional,
n/N
Difference (95% CI)
P
Value¶
Heterogeneous
(
I
2
Statistic)
Foods studied: variety of fruits and vegetables
9 9 253/3041 45 184/106 755 RD, 30% (37% to 23%) 0.001 Yes (94%)
Foods studied: apples, bell peppers, berries, bok choi, broccoli, cabbages, carrots, cucumber, leafy greens, lettuces, spring mix, scallions, spinach, summer squash,
tomatoes, and zucchini
5 5 63/803 39/1454 RD, 2.4% (1.5% to 6.3%)†† 1.00 Yes (58%)
Foods studied: barley, buckwheat, corn, mixed grains, rice, rye, and wheat
9 9 267/393 310/347 RD, 23% (37% to 8%) 0.043 Yes (89%)
Foods studied: baby multicereal, baby rice cereal, baby semolina, barley, buckwheat, corn, maize/tapioca, oats, rice, rye, spelt, and wheat
7 7 384/713 791/1641 RD, 11% (3% to 24%) 0.93 Yes (92%)
Foods studied: beet, bell peppers, cucumber, greens, green beans, lentil, oats, potatoes, purple amaranth, strawberries, tomatoes, and wheat
11 9 568‡‡ 470‡‡ SMD, 0.14 (0.74 to 0.46) 1.00 Yes (87%)
Foods studied: cucumber, greens, potato, strawberries, tomato, and wheat
8 7 207‡‡ 354‡‡ SMD, 0.38 (0.16 to 0.92) 0.98 Yes (75%)
Foods studied: results not synthesized
0NANANANA NANA
Foods studied: results not synthesized
0NANANANA NANA
Foods studied: oats and wheat
8 8 278‡‡ 275‡‡ SMD, 0.82 (1.19 to 0.45) 0.001 Yes (69%)
Foods studied: corn and wheat
4 4 198‡‡ 214‡‡ SMD, 0.21 (0.13 to 0.54) 1.00 Yes (62%)
ReviewOrganic Versus Conventional Foods
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plement 6) were heterogeneous and statistically insignifi-
cant. Several included studies reported that the season of
sampling and brand of milk affected fatty acid levels at
least as much as the farming method (93, 94, 123, 125).
We found no difference in the protein or fat content
of organic and conventional milk (Supplement 5). Results
were robust to removal of 1 study at a time. Too few
studies examined the protein and fat content of meats to
calculate summary effect sizes.
Contaminants
Pesticide Contamination
Detectable pesticide residues were found in 7% of or-
ganic produce samples (CI, 4% to 10%; 3041 samples)
and 38% of conventional produce samples (CI, 32% to
45%; 106 755 samples) (9 studies) (Table 2). Studies of
meats, poultry, eggs, and milk did not assess pesticide lev-
els. Organic produce had 30% lower risk for contamina-
tion with any detectable pesticide residue than conven-
tional produce (RD, 30% [CI, 37% to 23%]; P
0.001; I
2
94%; 9 studies) (Figure 2). This result was
statistically heterogeneous, potentially because of the vari-
able level of detection used among these studies.
Only 3 studies reported the prevalence of contamina-
tion exceeding maximum allowed limits; all were from the
European Union (159, 183, 263). One study was small (10
samples per group) and did not detect any pesticide resi-
dues exceeding maximum allowed limits in either group
(159). Differences in prevalence of contamination exceed-
ing maximum allowed limits were small among the other 2
studies (6% [60 of 1048 samples] for organic vs. 2% [179
of 2237 samples] for conventional [183], and 1% [1 of 266
samples] for organic vs. 1% [36 of 324 samples] for con-
ventional [263]).
Bacterial Contamination
Prevalence of E. coli contamination was 7% in organic
produce (CI, 4% to 11%; 826 samples) and 6% in con-
ventional produce (CI, 2% to 9%; 1454 samples)—not a
statistically significant difference (Figure 3) (RD, 2.4%
[CI, 1.5% to 6.2%]; P1.00; I
2
58%), although
only 5 studies examined this outcome. Four of these 5
studies found higher risk for contamination among organic
produce. In sensitivity analyses, when we removed the 1
study (of lettuce) that found higher contamination among
conventional produce, we found that organic produce had
a 5% greater risk for contamination than conventional al-
ternatives (RD, 5.1% [CI, 2.92% to 7.18%]; P0.001;
I
2
0%). No study detected Salmonella (90, 159, 205,
206, 214), enterohemorrhagic E. coli (90, 159, 205, 206,
214), or Listeria (214, 226) among produce samples.
Bacterial contamination is common among both or-
ganic and conventional animal products; however, differ-
Figure 2. RD of detecting any pesticide residues in organic and conventional fruits, vegetables, and grains.
Author (Reference)
Multiple-food studies
Andersen and Poulsen (75)
Baker et al (79)
Collins and Nassif (106)
Lesueur et al (183)
Poulsen and Andersen (231)
Tasiopoulou et al (263)
Single-food studies
Amvrazi and Albanis (74)
Hoogenboom et al (159)
Porretta (230)
Summary RD, all studies
Summary RD, excluding single-food studies
Heterogeneity: I2 = 94%
P Val ue
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
0.002
1.00
0.083
<0.001
<0.001
RD (95% CI), %
RD
–28 (–33 to –23)
–34 (–36 to –32)
–18 (–26 to –9)
–48 (–50 to –45)
–35 (–38 to –32)
–24 (–27 to –22)
–50 (–81 to –19)
0 (–17 to 17)
–40 (–85 to 5)
–30 (–37 to –23)
–32 (–39 to –25)
Organic
4/81
118/1291
14/118
100/1044
6/216
7/266
4/10
0/10
0/5
Conventional
Contaminated/Total, n/N
1354/4069
39 949/92 696
68/230
1272/2225
1582/4188
874/2342
81/90
0/10
2/5
Lower risk for
contamination in
or
g
anic
p
roduce
Higher risk for
contamination in
or
g
anic
p
roduce
–50% 0 50%
All studies sampled food from retail or wholesale settings except Hoogenboom and colleagues (159), which sampled directly from farms. Tasiopoulou and
colleagues (263) did not specify the study design, but because the testing was part of a governmental monitoring program, we assume that samples were
obtained from retail or wholesale settings, similar to the other government monitoring programs (75, 79, 231). We used a continuity correction of 0.5
(half a sample contaminated) for studies with 0 counts to allow RDs to be calculated. Removal of studies with 0 cells did not change results (see
Appendix, available at www.annals.org). All RDs are absolute RDs. Summary Pvalues are adjusted Pvalues. Funnel plots did not suggest publication
bias, and results were robust to removal of 1 study at a time. RD risk difference.
Review Organic Versus Conventional Foods
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ences in the prevalence of bacterial contamination between
organic and conventional animal products were statistically
insignificant (Figure 4). For chicken, 67% (CI, 42% to
93%) of organic samples and 64% (CI, 40% to 90%) of
conventional samples were contaminated with Campylobac-
ter and 35% (CI, 8% to 63%) of organic samples and 34%
(CI, 16% to 52%) of conventional samples were contam-
inated with Salmonella (3 studies).Pork was commonly
contaminated with E. coli (65% of organic and 49% of
conventional samples) (201), Salmonella (median, 5.1%;
range, 0% to 39%) (282), and Listeria monocytogenes (3%
of organic and 4% of conventional samples) (152). No
studies compared the contamination of organic and con-
ventional beef with human pathogens.
Antibiotic Resistance
The risk for isolating bacteria resistant to 3 or more
antibiotics was 33% higher among conventional chicken
and pork than organic alternatives (CI, 21% to 45%; P
0.001; I
2
62%; 5 studies) (Figure 5 [top panel] and
Supplement 7, available at www.annals.org). Results were
robust to removal of 1 study at a time. Bacteria isolated
from retail samples of organic chicken and pork had 35%
lower risk for resistance to ampicillin (RD, 34.9% [CI,
56.2% to 13.6%]; P0.031; I
2
90%; 5 studies)
(Figure 5 [bottom panel]), although removal of 1 study
rendered results statistically insignificant. Although com-
parisons for most of the remaining antibiotics suggest
greater resistance among bacteria isolated from conven-
tional compared with organic products, differences were
statistically insignificant (Supplement 8, available at www
.annals.org). Few studies examined resistance to the same
antibiotic on the same animal product, and effect sizes
were heterogeneous.
Fungal Toxin and Heavy Metal Contamination
The included studies demonstrate mixed results about
contamination of grains with fungal toxins. We found no
difference in risk for contamination with or mean levels of
ochratoxin A (Table 2). However, we found lower levels
and lower risk for contamination with deoxynivalenol in
organic grains than conventional alternatives (SMD,
0.82 [CI, 1.19 to 0.45]; P0.001; I
2
69; 8
studies; median difference, 34
g/kg [minimum differ-
ence, 426
g/kg; maximum difference, 72
g/kg]) (RD,
23% [CI, 37% to 8%]; P0.043; I
2
89; 9 stud-
ies). Results were similar in subgroup analyses by grain type
(Appendix, available at www.annals.org). Among studies of
produce,no significant differences in cadmium or lead
content were identified (Table 2). All results were
heterogeneous.
Heterogeneity and Subgroup Analyses
To explore causes of heterogeneity, we conducted sub-
group analyses by specific food, testing method (fresh vs.
dry weight, and peeled and washed vs. unpeeled and un-
washed), study design, and organic standard used. Results
remained heterogeneous when analyzed by food: No sig-
nificant differences were found in the ascorbic acid content
of cabbage (3 studies), carrots (3 studies), potatoes (3 stud-
ies), or tomatoes (9 studies);
-carotene content of toma-
toes (3 studies); or protein content of wheat (6 studies)
when grown organically versus conventionally. Subgroup
analyses by testing method, study design, and organic stan-
dard remained heterogeneous and did not change findings,
although sample sizes were smaller, limiting our ability to
detect significant differences.
Only 1 data set reported peeling and washing produce
before testing. However, the prevalence of contamination
Figure 3. RD of detecting
Escherichia coli
in organic and conventional fruits, vegetables, and grains.
Author (Reference)
Multiple-food studies
Bohaychuk et al (90)
Mukherjee et al (205)
Mukherjee et al (206)
Single-food studies
Oliveira et al (214)
Phillips and Harrison (226)
Summary RD, all studies
Heterogeneity: I2 = 58%
P Value
0.89
0.21
<0.001
0.120
0.154
1.00
RD (95% CI), %
RD
7.5 (1.3 to 13.0)
3.3 (–1.8 to 8.3)
4.9 (2.3 to 7.5)
9.7 (–2.5 to 22.0)
–4.8 (–11.3 to 1.8)
2.4 (–1.5 to 6.3)
Organic
7/80
5/98
34/473
16/72
4/103
Conventional
Contaminated/Total, n/N
47/567
2/108
13/645
9/72
9/104
Lower risk for
contamination in
or
g
anic
p
roduce
Higher risk for
contamination in
or
g
anic
p
roduce
–50% 0 50%
All RDs are absolute RDs. Summary Pvalue is an adjusted Pvalue. Funnel plot did not suggest publication bias. Removal of 1 study (225) rendered results
significant, suggesting higher contamination among organic produce (RD, 5.1% [95% CI, 2.92% to 7.18%]; P0.001; I
2
0%). All studies sampled foods
directly from farms, except Bohaychuk and colleagues (90), which sampled produce purchased in retail settings. RD risk difference.
ReviewOrganic Versus Conventional Foods
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in this study could not be compared with other studies
because of use of different levels of detection (79). One
study tested products for pesticide residues before and after
peeling, finding that pesticide residues were undetectable
in both organic and conventional samples once apples were
peeled (203).
Reporting and Publication Bias
Among nutrient studies of produce, those with null
findings tended to report results incompletely (hence, they
could not be included in summary effect size calculations),
suggesting publication bias (Table 1). For example, among
the 34 studies that evaluated phenol levels in produce, only
36 of the 102 comparisons (35%) found higher levels in
organic produce. However, only 24 of the 34 studies re-
ported sufficient data for analysis, and among these, we
found significantly higher levels of total phenols among
organic produce (Table 1). In addition, for total phenols
and several other nutrients in produce, funnel plots were
asymmetric, raising concern for publication bias. Similarly,
funnel plots of analyses of fatty acids in milk suggested
possible publication bias.
We adjusted Pvalues to assign significance to differ-
ences between organic and conventional foods due to the
multiple statistical comparisons. It may be reasonable to
use a less stringent criterion for the interpretation of con-
taminant results because consumers may have a lower
threshold in their desire to avoid harms. However, exami-
nation of unadjusted Pvalues changes the conclusions for
Figure 4. RD for contamination of organic and conventional meat products with bacterial pathogens.
Author (Reference)
Cui et al (51)
Han et al (146)
Soonthornchaikul (256)
Summary RD
Cui et al (51)
Lestari et al (181)
Izat et al (161)
Summary RD
Miranda et al (53)
Miranda et al (50)
Miranda et al (50)
Miranda et al (53)
Miranda et al (201)
Hellström et al (152)
Garmo et al (130)
Schwaiger et al (250)
Schwaiger et al (250)
Schwaiger et al (251)
Schwaiger et al (250)
Schwaiger et al (250)
Schwaiger et al (250)
Schwaiger et al (251)
Schwaiger et al (250)
Heterogeneity: I2 = 0% (Campylobacter)
Heterogeneity: I2 = 73% (Salmonella)
P Value
0.76
0.99
0.77
1.00
0.02
0.85
0.111
1.00
0.73
0.016
0.38
0.40
0.081
0.90
0.130
1.00
0.48
1.00
0.46
0.32
0.36
1.00
1.00
RD (95% CI), %
RD
2.0 (–10.6 to 14.5)
0.1 (–15.5 to 15.8)
–3.0 (–22.6 to 16.6)
0.4 (–8.3 to 9.2)
16.8 (2.7 to 31.0)
–1.2 (–14.1 to 11.7)
–18.8 (–41.8 to 4.3)
0.7 (–17.4 to 18.7)
–1.7 (–11.1 to 7.8)
19.5 (37.0 to 35.4)
8.1 (–10.0 to 26.2)
33.0 (–4.4 to 11.1)
15.6 (–1.9 to 33.0)
–0.4 (–6.6 to 5.7)
0.2 (0.0 to 0.4)
0.0 (–0.5 to 0.05)
0.3 (–0.4 to 0.9)
0.0 (–0.5 to 0.05)
–2.5 (–9.2 to 4.2)
0.5 (–0.5 to 1.5)
–0.8 (–2.4 to 0.9)
0.0 (–0.5 to 0.5)
0.0 (–4.8 to 4.8)
Organic
150/198
23/53
24/30
121/198
11/53
11/48
4/60
45/55
27/55
4/60
35/54
2/60
3/1948
0/400
1/400
0/399
0/40
3/400
4/400
0/399
0/40
Conventional
Contaminated/Total, n/N
45/61
61/141
25/30
27/61
31/141
10/24
5/60
38/61
25/61
2/60
33/67
3/80
0/2092
0/400
0/400
0/400
1/40
1/400
7/400
0/400
0/40
Food
Chicken
Chicken
Chicken
Chicken
Chicken
Chicken
Chicken
Chicken
Chicken
Chicken
Pork
Pork
Raw milk
Egg content
Egg content
Egg content
Egg content
Egg shell
Egg shell
Egg shell
Egg shell
Pathogen
(Genus)
Campylobacter
Campylobacter
Campylobacter
Campylobacter
Salmonella
Salmonella
Salmonella
Salmonella
Escherichia
Escherichia
Listeria
Yersinia
Escherichia
Listeria
Escherichia
Campylobacter
Escherichia
Salmonella
Listeria
Campylobacter
Escherichia
Salmonella
Listeria
Lower risk for
contamination in
organic products
Higher risk for
contamination in
organic products
–50% 0 50%
Meat samples were obtained from retail stores, milk samples were raw milk obtained from farms, and all egg samples were obtained directly from farms.
Risk difference is calculated as the risk for contamination in the organic group minus that in the conventional group; thus, a positive (negative) number
indicates more (less) contamination in organic products. All RDs are absolute RDs. Summary effect measures reported are results of random-effect
models. I
2
25% suggests heterogeneity. Summary Pvalues are adjusted Pvalues. Funnel plots did not suggest publication bias, and results were robust
to removal of 1 study at a time. All studies sampled products from retail or wholesale settings with 4 exceptions: Lestari and colleagues (181), Hellstrom
and colleagues (152), Garmo and colleagues (130), and Schwaiger and colleagues (250, 251) sampled foods obtained directly from farms. Results for
Salmonella in pork (282) are not reported in this figure because the authors reported only median prevalence of contamination. RD risk difference.
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only a few outcomes: specifically, differences in contami-
nation with bacteria resistant to cephalothin, sulfisoxazole,
and tetracycline (Supplement 7).
DISCUSSION
Consumers purchase organic foods for many reasons.
Despite the widespread perception that organically pro-
duced foods are more nutritious than conventional alter-
natives, we did not find robust evidence to support this
perception. Of the nutrients evaluated, only 1 comparison,
the phosphorus content of produce, demonstrated the su-
periority of organic foods (differences were statistically sig-
nificant and homogenous), although removal of 1 study
rendered this result statistically insignificant. Higher levels
of phosphorus in organic produce than in conventional
Figure 5. RD for isolating antibiotic-resistant bacteria in selected analyses.
Author (Reference)
Cui et al (51)
Lestari et al (181)
Miranda et al (50)
Miranda et al (53)
Miranda et al (201)
Summary RD
Heterogeneity: I2 = 62%
P Value
<0.001
0.61
<0.001
0.016
<0.001
<0.001
RD (95% CI), %
RD
–51.5 (–72.7 to –30.4)
–7.1 (–34.5 to 20.2)
–35.4 (–46.6 to –24.1)
–20.0 (–36.3 to –3.7)
–41.1 (–54.0 to –28.2)
–32.8 (–44.6 to –20.9)
Organic
11/91
3/12
14/105
13/60
16/90
Conventional
Resistant to 3 Antibiotics
Contaminated/Total, n/N
Resistant to Ampicillin
Contaminated/Total, n/N
14/22
18/56
56/115
25/60
53/90
Lower risk for
contamination in
organic products
Higher risk for
contamination in
organic products
–50% 050%
Author (Reference)
Lestari et al (181)
Cui et al (51)
Miranda et al (50)
Miranda et al (53)
Miranda et al (201)
Summary RD
Heterogeneity: I2 = 90%
P Value
0.82
<0.001
<0.001
0.001
<0.001
0.031
RD (95% CI), %
RD
1.9 (–14.25 to 18.0)
–60.3 (–80.8 to –39.9)
–32.0 (–44.1 to –19.9)
–26.7 (–43.1 to –10.3)
–57.8 (–69.7 to –45.9)
–34.9 (–56.2 to –13.6)
Organic
7/33
3/91
23/105
13/60
21/90
Conventional
18/93
14/22
62/115
29/60
73/90
Lower risk for
contamination in
or
g
anic
p
roducts
Higher risk for
contamination in
or
g
anic
p
roducts
–50% 0 50%
Risk difference is calculated as the risk for contamination in the organic group minus that in the conventional group; thus, a positive (negative) number
indicates more (less) contamination in the organic group. All RDs are absolute RDs. Summary Pvalues are adjusted Pvalues. The number of antibiotics
tested in the included studies ranged from 8 to 15 (median, 9.5). All summary effect measures reported are results of random-effects models. Funnel plots
did not suggest publication bias. All studies sampled food purchased in retail settings except Lestari and colleagues (181), which sampled animal products
obtained directly from farms. The top panel shows the difference in risk for detecting Escherichia coli, Salmonella species, and Enterobacteriaceae resistance
to at least 3 antibiotics in organic vs. conventional chicken and pork. One study (50) examined drug resistance patterns for 3 organisms (E. coli,Listeria,
and Staphylococcus aureus) identified on organic and conventional products. To avoid entering the same study twice in the analyses, we included only the
resistance patterns reported for E. coli. However, in sensitivity analysis, we included the results for Listeria instead of E. coli. The results did not
substantially change. Two studies (52, 53) reported antibiotic resistance patterns for different bacteria (Enterobacteriaceae [53] and Enterococcus species
[52]) obtained from the same population of retail packaged chicken. To avoid entering the same chickens in the synthesis twice, we included
Enterobacteriaceae results in the syntheses (reported above) because it is the family to which E. coli and Salmonella belong. In sensitivity analysis, we used
the Enterococcus results, which did not substantially change findings. Results were robust to removal of 1 study at a time from summary effect
estimate. The bottom panel shows the difference in risk for detecting E. coli,Salmonella species, and Enterobacteriaceae resistance to ampicillin in
organic vs. conventional chicken and pork. The result was not robust to removal of 1 study at a time from summary effect estimate. RD risk
difference.
ReviewOrganic Versus Conventional Foods
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produce is consistent with previous reviews (19, 20), al-
though it is unlikely to be clinically significant because
near-total starvation is needed to produce dietary phospho-
rus deficiency (287).
We also found statistically higher levels of total phe-
nols in organic produce,
-3 fatty acids in organic milk
and chicken, and vaccenic acid in organic chicken than in
conventional products, although these results were highly
heterogeneous and the number of studies examining fatty
acids was small (5). Our finding of higher levels of these
beneficial fatty acids in organic than in conventional milk
is consistent with another recent meta-analysis of these
outcomes (288). One study examining the breast milk of
mothers consuming strictly organic diets found higher lev-
els of trans-vaccenic acid (58), similar to our findings
among organic dairy products. Otherwise, studies measuring
nutrient levels among humans consuming organic and con-
ventional diets did not find consistent differences.
Our study has 3 additional key findings. First, conven-
tional produce has a 30% higher risk for pesticide contam-
ination than organic produce. However, the clinical signif-
icance of this finding is unclear because the difference in
risk for contamination with pesticide residue exceeding
maximum allowed limits may be small. One study found
that children switched to an organic diet for 5 days had
significantly lower levels of pesticide residue in their urine
(55), consistent with our findings among the food studies.
Second, we found no difference in the risk for con-
tamination of produce or animal products with pathogenic
bacteria. Both organic and conventional animal products
were commonly contaminated with Salmonella and Cam-
pylobacter species. The reported rates of contamination are
consistent with published contamination rates of U.S. re-
tail meat samples (289–291). However, with removal of 1
study, results suggested that organic produce has a higher
risk for contamination with E. coli, a finding that was both
homogeneous and statistically significant. Similarly, an ex-
ploratory case–control study suggested that human con-
sumption of organic meat in the winter is associated with
symptomatic Campylobacter infection (70). These prelimi-
nary findings need to be confirmed with additional re-
search. A recent U.S. study found that produce from
organic farms using manure for fertilization was at signifi-
cantly higher risk for contamination with E. coli than was
produce from organic farms not using animal waste (odds
ratio, 13.2 [CI, 2.6 to 61.2]) (292).
Third, we found that conventional chicken and pork
have a higher risk for contamination with bacteria resistant
to 3 or more antibiotics than were organic alternatives.
This increased prevalence of antibiotic resistance may be
related to the routine use of antibiotics in conventional
animal husbandry. However, the extent to which antibiotic
use for livestock contributes to antibiotic-resistant patho-
gens in humans continues to be debated (293) because
inappropriate use of antibiotics in humans is the major
cause of antibiotic-resistant infections in humans. A previ-
ous review (23) reported that ciprofloxacin-resistant Cam-
pylobacter was more common among conventional than
organic chickens, a finding that our study did not detect.
Unlike the previous study, most of our included studies
were done after bans on fluoroquinolone use and we ex-
cluded fecal samples. As a precaution, the European Union
banned the use of some antibiotics in animal feed for
growth promotion in 2006 (294), and the United States
banned the use of enrofloxacin in 2005 (295).
Finally, there have been no long-term studies of health
outcomes of populations consuming predominantly or-
ganic versus conventionally produced food controlling for
socioeconomic factors; such studies would be expensive to
conduct. Only 3 short observational studies examined a
very limited set of clinical outcomes: 2 studies evaluating
allergic outcomes of a cohort of children consuming or-
ganic versus conventional diets in Europe found no asso-
ciation between diet and allergic outcomes (61, 64).
Our results should be interpreted with caution because
summary effect estimates were highly heterogeneous.
Three potential sources of heterogeneity are study methods
(for example, measurement and sampling methods, study
design, or organic standard used), physical factors (for ex-
ample, season, weather, soil type, ripeness, cultivar, or stor-
age practices [14, 111, 165, 171, 296]), and variation
within organic practices.
For example, heterogeneity among studies of pesticide
contamination likely reflects variation in the sensitivity of
testing methods and differences in pesticide contamination
by food type and country of origin (75, 297). To explore
causes of heterogeneity, we conducted subgroup analyses
by study design, assay method (fresh vs. dry weight), and
organic standard used in the study; however, these sub-
analyses did not reduce observed heterogeneity.
Too few studies for any 1 outcome reported informa-
tion about physical factors to conduct subgroup analyses,
although many studies controlled for these factors (for ex-
ample, 86% of meat studies specified sampling both pro-
duction systems during the same season and approximately
60% of comparison produce pairs were of the same cultivar
and harvested from neighboring farms). Many studies
noted that season of sampling and brand of milk were
important determinants of nutrient and fatty acid levels
(93, 94, 123, 125) because organic and conventional cows
may have similar diets in the winter but different diets in
the summer when grass is available for organic cows.
Finally, variation within organic practices (even if cer-
tified under the same standard) may also explain heteroge-
neity. A review of organic practices concluded that “varia-
tion within organic and conventional farming systems is
likely as large as differences between the two systems”
(298). For example, the use and handling of manure fer-
tilizers (a risk factor for bacterial contamination) varies
among organic farms (292).
Our study has several additional limitations. First, pro-
duce studies, most of which were experimental field stud-
Review Organic Versus Conventional Foods
358 4 September 2012 Annals of Internal Medicine Volume 157 • Number 5 www.annals.org
Downloaded From: http://annals.org/ by a Stanford Univ Medical Ctr User on 07/24/2015
ies, may not reflect real-world organic practices. Subgroup
analyses by study design did not change conclusions, al-
though sample sizes were small. Additionally, studies with
null findings frequently failed to adequately report results,
potentially biasing our study to find differences where
none exist. Finally, milk results should be interpreted with
caution because most milk studies examined raw rather
than pasteurized milk.
In summary, our comprehensive review of the pub-
lished literature on the comparative health outcomes, nu-
trition, and safety of organic and conventional foods iden-
tified limited evidence for the superiority of organic foods.
The evidence does not suggest marked health benefits from
consuming organic versus conventional foods, although or-
ganic produce may reduce exposure to pesticide residues
and organic chicken and pork may reduce exposure to
antibiotic-resistant bacteria.
From Veterans Affairs Palo Alto Health Care System, Palo Alto, Califor-
nia; Division of General Medical Disciplines and Lane Medical Library,
Stanford School of Medicine, Stanford, California; and Center for
Health Policy/Center for Primary Care Outcomes Research, Department
of Management Science & Engineering, and Department of Statistics,
Stanford University, Stanford, California.
Note: As the corresponding author and guarantor of the manuscript,
Crystal Smith-Spangler, MD, MS, takes full responsibility for the work
as a whole, including the study design, access to data, and decision to
submit the manuscript for publication.
Acknowledgment: The authors thank the staff of DocXpress at Lane
Medical Library for document retrieval.
Financial Support: Ms. Pearson was supported by a Stanford Under-
graduate Research Grant.
Potential Conflicts of Interest: None disclosed. Forms can be viewed at
www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum
M12-0192.
Requests for Single Reprints: Crystal Smith-Spangler, MD, MS, Stan-
ford Center for Health Policy and Center for Primary Care and Out-
comes Research, 117 Encina Commons, Stanford University, Stanford,
CA 94305-6019; e-mail, csmithsp@stanford.edu.
Current author addresses and author contributions are available at
www.annals.org.
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Current Author Addresses: Dr. Smith-Spangler: Division of General
Medical Disciplines, Stanford University, 1265 Welch Road, Medical
School Office Building, MC 5411, Stanford, CA 94305.
Dr. Brandeau: Department of Management Science and Engineering,
Huang Engineering Center, Room 262, Stanford University, Stanford,
CA 94205-4026.
Ms. Hunter, Mr. Bavinger, Ms. Pearson, Mr. Eschbach, Ms. Sundaram,
and Drs. Liu and Bravata: Center for Health Policy, Stanford University,
117 Encina Commons, Stanford, CA 94305-6019.
Dr. Schirmer: Veterans Affairs Palo Alto Health Care System, 3801
Miranda Avenue (132), Palo Alto, CA 94304.
Mr. Stave: Lane Medical Library, 300 Pasteur Drive, L-109, Stanford,
CA 94305-5123.
Dr. Olkin: Department of Statistics, Sequoia Hall, 390 Serra Mall, Stan-
ford University, Stanford, CA 94305-4065.
Author Contributions: Conception and design: C. Smith-Spangler, J.C.
Bavinger, M. Pearson, V. Sundaram, D.M. Bravata, I. Olkin.
Analysis and interpretation of the data: C. Smith-Spangler, M.L. Bran-
deau, G.E. Hunter, J.C. Bavinger, M. Pearson, P.J. Eschbach,
V. Sundaram, P. Schirmer, D.M. Bravata, I. Olkin.
Drafting of the article: C. Smith-Spangler, M.L. Brandeau, J.C. Bav-
inger, V. Sundaram, P. Schirmer, D.M. Bravata.
Critical revision of the article for important intellectual content:
C. Smith-Spangler, M.L. Brandeau, V. Sundaram, H. Liu, D.M. Bravata,
I. Olkin.
Final approval of the article: C. Smith-Spangler, M.L. Brandeau, J.C.
Bavinger, P.J. Eschbach, V. Sundaram, H. Liu, P. Schirmer, D.M. Bra-
vata, I. Olkin.
Provision of study materials or patients: C. Smith-Spangler, D.M.
Bravata.
Statistical expertise: C. Smith-Spangler, D.M. Bravata, I. Olkin.
Administrative, technical, or logistic support: G.E. Hunter, M. Pearson,
C. Stave.
Collection and assembly of data: C. Smith-Spangler, M.L. Brandeau,
G.E. Hunter, J.C. Bavinger, M. Pearson, P.J. Eschbach, V. Sundaram,
H. Liu, P. Schirmer, C. Stave, D.M. Bravata.
APPENDIX:SUPPLEMENTAL INFORMATION ABOUT
STATISTICAL ANALYSES AND OUTCOMES THAT COULD
NOT BESYNTHESIZED
Continuity Correction
In an effort to include all eligible studies, a continuity cor-
rection was applied for studies with 0 events in 1 or more groups.
In practice, we applied the continuity correction in 2 analyses:
contamination with any pesticide residues (Figure 2) and con-
tamination of chicken or pork with bacteria resistant to cipro-
floxacin.
Among the 9 pesticide contamination studies, 2 had 0
events (Figure 2). These were small, single-food studies. Removal
of the small studies with 0 events did not substantially change
results (Figure 2).
Among the contamination of chicken or pork with bacteria
resistant to ciprofloxacin, removal of the 2 studies with 0 events
(146, 256) did not substantially change results, although only 3
studies remained for analysis (RD, 4% [CI, 25% to 17%];
P1.00, I
2
93%).
Results were not synthesized if the number of studies was
less than 3 after those studies with 0 events were removed. This
was the case with pesticide residues exceeding maximum allowed
limits (we report a range); contamination of milk with S. aureus
resistant to erythromycin, oxacillin, and tetracycline; and con-
tamination of chicken and pork with bacteria resistant to doxy-
cycline and gentamicin.
Other Nutrients in Produce
Too few studies evaluated selenium, manganese, zinc, and
vitamins B, D, and K to be synthesized (Supplement 2).
Other Nutrients in Animal Products
Only 3 studies (110, 129, 153) evaluated the calcium con-
tent of milk: 2 studies (129, 153) reported no difference by
farming method and the other (110) reported significantly higher
levels of calcium in organically produced milk (P0.010). Two
studies evaluated the lutein and zeaxanthin content of milk (93,
255), finding significantly higher levels of both antioxidants in
organic than conventional milk. Two studies examined the zinc
content of eggs (132) and beef products (216), finding signifi-
cantly less zinc in organic egg yolks and beef kidney and sig-
nificantly more zinc in beef muscle than their conventional
counterparts.
Two studies compared protein content of chicken: 1 study
found significantly more protein in organic than conventional
chicken (160) and the other found no difference (192).
Botanical Pesticides in Produce
Two studies (95, 172) tested for 2 botanical pesticides al-
lowed in organic cultivation: Neither pesticide was detectable in
organic or conventional produce samples.
Antibiotic Resistance of Bacteria in Produce
Only 1 study examined the prevalence of antibiotic resis-
tance in bacteria in produce, finding no difference between or-
ganic and conventional produce (245).
Subgroup Analyses of Deoxynivalenol and Ochratoxin A
in Produce
In subgroup analyses, we found a higher risk for ochratoxin
A (OTA) contamination in organically grown rice (84, 133, 166)
(RD, 35% [CI, 17% to 53%]; P0.001; I
2
22) but not in
wheat (84, 111, 164, 166, 189, 235) compared with conven-
tional alternatives.
Seven studies examined deoxynivalenol levels in wheat (135,
150, 224, 235, 243, 249, 270), finding significantly lower levels
of deoxynivalenol in organic wheat (SMD, 0.94 [CI, 1.27 to
0.62]; P0.001; I
2
63), although 1 large study, which did
not report sufficient detail to be included in summary effect size
calculations, found no significant differences in deoxynivalenol
concentrations (122).
Other Fungal Toxin Results in Milk and Meats
Two studies evaluated mycotoxin contamination of milk: 1
study found significantly higher levels of aflatoxin in organic than
conventional milk (131), whereas another study found no differ-
ence in OTA contamination (253). One study found that OTA
contamination of porcine serum samples was significantly higher
among organic than conventional samples (1.32 vs. 0.16
g/kg;
P0.001) (232).
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Two studies evaluated mycotoxin contamination of milk:
1 study found significantly higher levels of aflatoxin in organic
than conventional milk (131), whereas another study found
no difference in OTA contamination (253). One study found
that OTA contamination of porcine serum samples was sig-
nificantly higher among organic than conventional samples
(1.32 vs. 0.16
g/kg; P0.001) (232).
Appendix Figure 1. Summary of evidence search and selection.
Full-text articles reviewed
(n = 460)
Potentially relevant articles (n = 5908)
MEDLINE: 3381
CAB Direct: 827
Cochrane Library: 51
Agricola: 1391
TOXNET: 204
EMBASE: 4
Bibliographic and
manual search: 50 Excluded (n = 5448)
Not an organic or conventional food study: 5221
Not peer-reviewed: 30
Single-group study: 42
Review: 26
Nonresearch: 32
Consumer beliefs: 29
Consensus statement: 10
Not a study food: 32
Not an outcome of interest: 26
Excluded (n = 223)
Not an organic or conventional food study: 44
Not English-language study: 2
Not an included food: 39
Single-group study: 8
Fertilizer study: 15
Nonresearch opinion: 6
Abstract only: 19
Consumer beliefs or perceptions: 1
Not peer-reviewed: 2
Not an outcome of interest: 81
No statistical tests performed: 6
Articles meeting inclusion criteria
(n = 237)
Studies of
human diets
(n = 17*)
Studies of
foods
(n = 223*)
* Three studies reported on human diets and on the foods themselves.
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Appendix Figure 2. Selected characteristics of included studies.
Studies Without
Characteristic, n
Studies With
Characteristic, n
Studies Without
Characteristic, n
Studies With
Characteristic, n
Randomized study
Study reported the organic standard used
Study linked outcomes with health outcomes for humans
Study not funded by an organization with interests in the
outcome
Study reported obtaining IRB approval and participant consent
Organic group consumed predominantly organic foods
(vs. organic group consuming 1 organically grown food)
15 0 5510 1510
Harvesting or processing method the same for both groups
Study reported the organic standard used
Study reported sample size
Study not funded by an organization with interests in
the outcome
Sample size the same for both groups
150 0 2502001501005050100
The top panel presents the characteristics of the included human studies. Seventeen publications compared the human health effects of consuming
organic vs. conventional food. Three publications report data from the same population and are counted only once in the figure. Hence, the number of
studies sums to 14. The bottom panel presents the characteristics of the 223 included studies of food. IRB institutional review board.
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CORRECTION:ARE ORGANIC FOODS SAFER OR
HEALTHIER THAN CONVENTIONAL ALTERNATIVES?
AS
YSTEMATIC REVIEW
In Figure 2 of a recent article (1), the conventional number for
the study by Tasiopoulou et al should be 2342, not 3242.
The last sentence of the “Pesticide Contamination” section on
page 354 should read as follows: Differences in prevalence of con-
tamination exceeding maximum allowed limits were small among
the other 2 studies (6% [60 of 1048 samples] for organic vs. 2%
[179 of 2237 samples] for conventional [183], and 1% [1 of 266
samples] for organic vs. 1% [36 of 324 samples] for conventional
[263]).
In Table 1 and Supplement 2, the word “flavanols” should be
“flavanoids.” In Figure 5, the word “produce” in the figure labels
should be “product.”
Reference
1. Smith-Spangler C, Brandeau ML, Hunter GE, Bavinger JC, Pearson M, Eschbach
PJ, et al. Are organic foods safer or healthier than conventional alternatives? A system-
atic review. Ann Intern Med. 2012;157:348-66.
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  • ... More specifically, research shows that organic food production is likely more environmentally sustainable (Bahlai, Xue, McCreary, Schaafsma, & Hallett, 2010;Crowder, Northfield, Strand, & Snyder, 2010) but, as previously shown, many consumers also believe that organic food products are more healthful than their conventional counterparts (Lee et al., 2013). Superior health attributes would be an important argument for organic production, but, so far, evidence supporting this claim is mixed, at best (Barański et al., 2014;Dangour et al., 2009;Smith-Spangler et al., 2012). ...
    ... More specifically, products that bear the organic label are judged as being lower in calories, with better nutritional content, and they therefore elicit greater willingness to pay. Since there is currently no conclusive evidence to support these beliefs about organic food products (Barański et al., 2014;Dangour et al., 2009;Smith-Spangler et al., 2012), it is generally considered that decision makers are biased towards thinking that organic food products are more healthful than conventional food products. Therefore, in both examples, i.e. low-fat claim and organic label, decision makers' behaviour is described as influenced by a specific heuristic, namely the health halo effect. ...
    ... Specifically, it has been shown that organic food products are perceived as being more healthful (Hughner, McDonagh, Prothero, Shultz, & Stanton, 2007;Lee et al., 2013;Orquin & Scholderer, 2015;Schuldt & Hannahan, 2013;Schuldt & Schwarz, 2010;Sörqvist et al., 2015), safer (Michaelidou & Hassan, 2008) and of better quality (Lockie, Lyons, Lawrence, & Mummery, 2002). Since there is currently no conclusive evidence that organic food products are indeed more healthful than conventional alternatives (Barański et al., 2014;Dangour et al., 2009;Smith-Spangler et al., 2012), it is often concluded that decision makers have an irrational bias in favour of organic food products (EUFIC review, 2013). ...
    Thesis
    Full-text available
    This doctoral dissertation makes a twofold contribution to the understanding of psychological processes behind food choice. First, it explores whether cognitive shortcuts, known as heuristics, based on seemingly irrational beliefs can lead to rational behaviours when applied in the right context. One such heuristic, the organic = healthful heuristic, is explored. It is the belief that organic products are more healthful than conventional products. There is no conclusive evidence supporting this belief, also known as the halo effect, where positive attitudes towards organic products transfer to beliefs about specific properties such as healthfulness. Here I propose statistical learning as an alternative explanation to the halo effect, and test this in three studies. Study 1 shows that food products from healthful food categories are more likely to be organic. Study 2 shows that consumer perceptions of the healthfulness and the number of organic products across food categories are accurate. Study 3 shows that consumers perceive organic products as more healthful when the statistical structure justifies this inference. These findings show that consumers correctly use organic products as a cue for healthfulness because they are, on average, 30% more healthful than conventional products. Second, this doctoral dissertation develops a new information search measure which complements existing measures to better describe consumer search processes. One area, which is currently not covered by existing measures, is when information search consists of equal amounts of attribute- and alternative-wise search sequences. I propose a new measure, the Systematicity of Search Index (SSI), which explores information search in terms of systematicity or the proportion of non-random search. Study 4 demonstrates the usefulness of the measure and shows that the SSI can shed light on processes not captured by the existing measures for analysing information search.
  • ... Organic production has become increasingly important worldwide, as a potential alternative to conventional intensive agriculture, due to great concerns about the environment, food safety, and human health [1][2][3]. In developed countries, demand for organic products is steadily rising and a relevant proportion of food consumed comes from organic sources [4]. ...
    ... Considering the definition and the principles of organic production, the consumption of organic foods may reduce exposure to nitrate and pesticide residues due to the strict limitation of the use of chemically synthesized inputs [3,8]. However, the significance of these differences is questionable, because actual levels of contamination in organic and conventional foods are generally well below acceptable limits [9] and in general the proximity to sources of contamination (e.g., traffic, chemical industries) seems to have a crucial role in the occurrence of environmental pollutants in foodstuffs [10]. ...
    Article
    Full-text available
    The market for organic products is growing rapidly, probably attributable to the general customer perception that they are healthier foods, with a better nutritional profile than conventional ones. Despite this, the available studies show limited differences in the nutrient profile of organically and conventionally primary food products. Apart from this literature, no studies have focused on the nutrition profile of commercially prepacked foods. Thus, the aim of the present survey was to compare the nutritional quality intended as nutrition facts of organic and conventional prepacked foods sold in Italy. A total of 569 pairs of prepacked products (organic and their conventional counterparts) were selected from nine food categories sold by online retailers. By comparing organic and conventional products in the “pasta, rice and other cereals” category, the former were lower in energy, protein, and higher in saturates compared to the latter. Organic “jams, chocolate spreads and honey” products were lower in energy, carbohydrates, sugars and higher in protein than their regular counterparts. No differences were found for energy, macronutrients and salt for other categories. Therefore, based on the mandatory information printed on their packaging, prepacked organic products are not of a superior nutritional quality than conventional ones, with just a few exceptions. Consequently, the present study suggests that organic certification cannot be considered an indication of better overall nutritional quality. Further studies examining the nutritional quality of organic foods, taking into account the ingredients used, might better explain the results obtained.
  • ... A commonly made distinction between EOs is whether they are obtained from plants grown by organic or conventional farming. Organic farming is considered superior over conventional farming by most consumers 335,336 . It is believed that this also results in a difference in the therapeutic potencies of the EOs produced. ...
    ... Furthermore, organic products are often believed to be more nutritious and/or healthier than conventional products. However, most research on this matter is inconclusive 335,336,[392][393][394][395][396] . ...
    Thesis
    Full-text available
    The increasing level of antimicrobial resistance poses the threat that no suitable antimicrobials will be available for systematic treatment of common diseases. More and more Candida infections are caused by intrinsically and multi-resistant Candida isolates. There is clearly renewed scientific interest in discovering drugs from natural sources, although natural product-based drug discovery is considered intrinsically complex and requires a highly integrated interdisciplinary approach. Medicinal plants that are used to treat infectious diseases appear to be an abundant source of new bioactive secondary metabolites. One such class of plant-based molecules are essential oils which have been used therapeutically for millennia as they have a broad range of biological activities.
  • ... In addition, the price premium for purchasing HF products was not related to the HSR. Other research has reported similar findings, with foods labelled 'organic' found to have a similar nutrition profile but cost significantly more than those that are not [50,63,64]. This is of significance as the use of 'buzzwords', along with higher price points, have been found to strongly influence consumers and generate a misleading health halo effect [13,15,17,29,31,32,65]. Consumers should have the right to seek and pay a premium for ethical, organic and sustainable food options, though this should not be confused with purchasing healthier choices. ...
    Article
    Full-text available
    Growth in the consumer health and wellness industry has led to an increase of packaged foods marketed as health food (HF) products. In consequence, a ‘health halo’ around packaged HF has arisen that influences consumers at point-of-purchase. This study compared product claims (nutrient content claims (NCC), health claims and marketing ‘buzzwords’) displayed on packaged HF snack products sold in HF stores and HF aisles in supermarkets to equivalent products sold in regular aisles (RA) of supermarkets. Product Health Star Rating (HSR), nutrient profile and price were also compared. Data were collected for 2361 products from three supermarket chains, two HF chains and one independent HF store in Sydney, Australia. Mann-Whitney U tests compared the product claims, HSR, nutrient composition and unit ($) price. HF snacks displayed significantly more product claims per product compared to RA foods (HSR ≤ 2.5), median (IQR) 5.0(4.0) versus 1.0(2) and (HSR > 2.5) 4.0(4.0) versus 3.0(4), respectively (p < 0.001). A significantly different HSR was evident between HF and RA snack products, median 2.5(0) versus 2.0(1.5), respectively (p < 0.001). HF snacks cost significantly more than RA snack foods, irrespective of product HSR (p < 0.001). These findings support the recommendation for revised labelling regulations and increased education regarding consumers food label interpretation.
  • ... Однако в отдельных исследованиях было показано, что органические пищевые продукты содержат больше фосфора [12] и омега-3-ненасыщенных жирных кислот [13]. Бактерии кишечной группы выявлялись одинаково часто как в органических, так и в обычных продуктах, но в обычных продуктах чаще выявлялись штаммы, устойчивые к антибиотикам [14]. ...
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    Full-text available
    Aim. To provide a definition and classification of nutraceutical products and to show their significane in modern integrative medicine. Background. Nutraceuticals are foodstuffs and their components, which have a positive effect on human health, including preventive maintenance and treatment of diseases. Nutraceuticals include healthy and functional foods, as well as biologically active food additives (BAFA). Healthy foods are nutritional foodstuffs without any artificial modification. These include organic, whole, and natural foods. Alongside a high nutritional value, functional food products have a positive effect on the human body due to functional food ingredients. BAFAs are food additives that contains one or several food ingredients (vitamins, mineral substances, plant components, amino acids and others). Specialists express conflicting viewpoints concerning nutraceuticals. Some nutraceuticals, such as probiotics, have confirmed their effectiveness in clinical trials, while the beneficial properties of others require further elucidation. Conclusions. The application of nutraceuticals, as well as their combined use with pharmaceuticals, in accordance with recommendations by scientific professional associations formulated on the basis of valid research studies can lead to an improvement in the quality of the life and longevity of the population. This position forms a basis for the development of integrative medicine — a contemporary approach to the treatment of diseases.
  • ... Regarding nutritional proprieties, the literature about Zn and Fe content in organic and conventional food is very contradictory: some studies showed a higher content of Fe and Zn in the organic crops (Vr cek et al. 2014), others in the conventional ones (Ciołek et al. 2012;Drakou et al. 2015;Kristl et al. 2013). A meta-analysis study reported a major content of Ca, Mg, K and P in organic food but the authors concluded that only the data about P can be considered statistically significant (Smith-Spangler et al. 2012). The same study showed that protein content is lower in organic fruits and vegetables, as well as fiber content, even though the results were not considered significant. ...
    Article
    Climate change, with increasing temperatures and atmospheric carbon dioxide levels, constitutes a severe threat to the environment and all living organisms. In particular, numerous studies suggest severe consequences for the health of crop plants, affecting both the productivity and quality of raw material destined to the food industry. Of particular concern is the reduction of proteins and essential micronutrients as iron and zinc in crops. Fighting this alarming trends is the challenge of Climate-Smart Agriculture with the double goal of reducing environmental impacts (use of pesticides, nitrogen and phosphorus leaching, soil erosion, water depletion and contamination) and improving raw material and consequently food quality. Organic farming, biofertilizers and to a lesser extent nano-carriers, improve the antioxidant properties of fruits, but the data about proteins and micronutrients are rather contradictory. On the other hand, advanced devices and Precision Agriculture allow the cultivations to be more profitable, efficient, contributing more and more to reduce pest diseases and to increase the quality of agricultural products and food safety. Thus, nowadays adoption of technologies applied to sustainable farming systems is a challenging and dynamic issue for facing negative trends due to environmental impacts and climate changes.
  • ... These results are also confirmed by a more recent version of the Eurobarometer published after the literature search (EFSA, 2019).10 Organic food products may reduce the intake of PPP residues but have been shown to be partially contaminated(Smith-Spangler et al., 2012).11 Additionally, the Eurobarometer, published after the literature search, indicates that European consumers react differently to information on food risks in general: some indicate changes in their behavior while others do not, although the latter remain concerned (EFSA, 2019). ...
    Article
    Full-text available
    Food safety has a significant influence on food markets and is of great societal importance because it protects human health and life. Most studies presume that the presence or absence of food safety can be objectively assessed based on data from natural sciences and might be further interpreted and perceived in different ways; however, there is no consensus on the definition of food safety. Disputes within the scientific community and increasing public discourse suggest that there is no generally accepted definition of what is “safe” or “unsafe”. This paper introduces a framework that describes food safety in a broader sense, using the example of plant protection products, by identifying different evidence practices through the classification of criteria from various research fields. Data were collected in an integrative literature review. Criteria for assessing food safety were classified and collected within a conceptual framework that acknowledged the multidisciplinarity of knowledge bases. The analysis highlights the questions that arise when determining these criteria. We conclude that obtaining a generalized definition of food safety is not possible. Instead, our results showed the determination of food safety by criteria at different levels: science-based criteria at knowledge and value levels that result in standards and consumer-based criteria at knowledge and value levels that result in behavior. A better understanding of food safety criteria helps to show deficits in the current risk analysis practice and points to solutions for more consistent regulations, leading to more stable market conditions and a stronger mutual understanding.
  • ... The quality difference between organic and conventional food is an expression of preferences based on claims of organic food's positive effects on, e.g., health, environment, animal welfare and taste. Although these claims are not undisputed (see e.g., Barański et al., 2017;Smith-Spangler et al., 2012;and Dangour et al., 2009 for organic food's nutritional aspect, and e.g., Tuomisto et al., 2012;and Bahlai et al., 2010 for its environmental aspect), it is undeniably so that organic food entails higher prices than conventional food, ceteris paribus, reflecting higher production costs, smaller packaging sizes, etc., and a perceived or actual quality difference. If this was not the case, the GPP policy from 2006 would be redundant. ...
    Article
    This paper studies a Green Public Procurement (GPP) policy decided by the Swedish government in 2006, stating objectives related to organic farming. The policy aims to increase the public sector's organic food purchases, in order to incentivise Swedish farmers to convert to organic practices, thereby contributing to national environmental quality objectives. We analyse the effect of organic food procurement on organic agricultural land, using panel data from 2003 to 2016 including information on municipalities' organic food purchases, land use, and direct subsidies aimed at organic production. Based on different specifications and mainly FGLS estimations, we conclude that the 2006 organic food policy is associated with a significant positive impact on organic agricultural land. A significant effect of direct agricultural policy in the form of subsidies is also found.
  • Article
    Objective To investigate the influence of current food and nutrition trends on dietitians’ perceptions of the healthiness of packaged foods. Design This observational study used a cross-sectional survey. Participants rated (strongly disagree to strongly agree) the extent to which a range of factors, independent of the energy, nutrient and ingredient content, influenced their perceptions of the healthiness of packaged foods. Two open-ended questions allowed for participants to list additional items they considered important. Setting Online survey. Participants Australian dietitians ( n 117). Results The greatest consensus was a positive influence of the fit within the core food groups and presence of seasonal ingredients, and a negative influence of an increasing number of additives. Mixed opinions were obtained for GM ingredients, locally sourced ingredients, labelling of animal welfare and organic certification. Nutritional indicators received a split where almost half of participants disagreed/strongly disagreed that they positively influenced their perception of healthiness. Content analysis of open-ended responses ( n 53, 45 %) revealed four broad categories as important in considering healthiness: ‘a whole food approach’, ‘marketing and labelling’, ‘product information’ and ‘context of diet’. A small number of responses (count of 6, 5 %) reported that packaging, advertising and features such as celebrity endorsement were a negative influence. Conclusions Dietitians have a broad concept of the healthiness of packaged foods, which incorporates elements of food safety, wholeness of the ingredients and marketing. Providing unified messages to the consumer can help to build the public perception of dietitians as experts in nutrition advice and counselling.
Literature Review
  • Article
    Background Organic farming is a production technique that imposes major restrictions on the use of fertilizers, pesticides, feed additives and veterinary drugs and for this reason consumers perceive organic foods to be healthier. The content of health-promoting molecules such as ascorbic acid, β-carotene, lycopene and salicylic acid are important aspects of the nutritional quality of organic foods. Aim To evaluate health promoting substances and the heavy metal content of tomato berries grown using conventional, integrated pest management (IPM) and organic farming techniques. Methods Moisture was determined by drying, crude protein by the Kjeldhal method, and ashes by incineration at 550°C. Ergosterol, ascorbic acid, β-carotene, lycopene and salicylic acid were determined by HPLC. The levels of heavy metals were measured by atomic absorption spectroscopy. Results Compared to crops grown using conventional and IPM methods, organic tomatoes contained more salicylic acid but less vitamin C and lycopene. Organic tomatoes had higher Cd and Pb levels but a lower Cu content. Organic fruits had a slightly higher protein content than conventionally cultivated fruits, but the difference was minimal and consequently the nutritive significance was poor. Conclusions Farming techniques may have an impact on the quality of tomatoes. Their higher salicylate content supports the notion that organic foodstuffs are more wholesome. However, the lower lycopene and ascorbic acid levels of organic tomatoes are not to be regarded as positive. No residues of pesticides and ergosterol were detected.
  • Article
    As the largest group of phytochemicals, dietary phenolics play an important role in human health and disease prevention. Cultural practices have been shown to have the potential for affecting phenolic compounds in food crops. Spring and summer trials were conducted in 2003 to examine the effects of organic fertilization and high tunnel environments on phenolic constituents of lettuce (Lactuca sativa L.) cultivars Red Sails and Kalura. Effects of postharvest storage at 4 degrees C for 16 days on total phenolics of lettuce harvested from the summer trial were also evaluated. Total phenolics, excluding anthocyanins, were measured spectrophotometrically, and major phenolic constituents were identified and quantified by high-performance liquid chromatography. Chlorogenic acid and quereetin glycosides were found to be predominant in lettuce. 'Red Sails' consistently exhibited significantly higher phenolic concentrations than 'Kalura'. Organic (compost + fish emulsion) and conventional (N-P-K + CaNO3) fertilization did not consistently differentially affect lettuce phenolics in our recently established organic and conventional plots. The high tunnel environment generally reduced phenolic levels in lettuce relative to the open field. However, differences between high tunnel and open field varied with cultivar and season. Effects of production factors on lettuce phenolics were maintained during cold storage. There was a substantial increase in total phenolics during storage, likely correlated with declining lettuce quality. Further studies are warranted to more fully assess the impact of cultivar and production management, including organic fertilization, on lettuce phenolics.
  • Article
    Full-text available
    Despite being the commonest bacterial cause of infectious intestinal disease (11D) in England and Wales, outbreaks of campylobacter infection are rarely reported. However, data from the Campylobacter Sentinel Surveillance Scheme suggested that outbreaks might be more common than was previously suspected, since a high proportion of cases reported other illness in the home or in the community at the same time as their illness. To identify factors that might lead to these apparent outbreaks, the exposures of cases of Campylobacter jejuni infection reporting other illness, either in the home or the community, were compared with those for cases not reporting other illness using case-case methodology. Illness in the home was associated with consuming organic meats in the winter, having contact with a pet suffering from diarrhoea or visiting a farm in the 2 weeks before the onset of symptoms. Illness in the community was associated with the consumption of foods in restaurants or drinking unpasteurized milk. Prevention of campylobacter infection requires that better methods of outbreak detection and investigation are developed, which in turn should lead to a better understanding of risk factors.
  • Article
    Three year trials were conducted to investigate the set of spring barley varieties cultivated according to principles of ecological agriculture or using the ordinary agrotechnics (fertilization, seed treatment, herbicides, fungicides, insecticides). The weather conditions affected most of the quality traits more than e.g. nitrogen fertilization or system of cultivation. Significant differences among years were recorded in protein content in grain, relative extract at 45 °C, Kolbach index, diastatic power, and apparent final attenuation. The cultivation system substantially influenced the β-glucan content in wort, it was surprisingly low under ecological system of cultivation. The effect of the cultivation system was also proved in the hot water extract and partially in Kolbach index and friability.
  • Article
    A field experiment was carried out during 2002-03 and 2003-04 to study the response of organic amendments and biofertilizers on growth, yield and quality attributes of Chinese cabbage (Brassica pekinensis (Lour.) Rupr.). Combined use of organic amendments coupled with seedling inoculation in either phosphate solubilizing microorganisms or vesicular arbuscular mychorrhizae registered head yield at par to control (conventional fertilization). Sole application of farmyard manure or digested sludge and/or its combined use with phosphate solubilizing microorganisms significantly increased the dry matter and total carbohydrate content of head. In comparison to conventional fertilization, the vitamin C content in head was noticed 43.8% more in farmyard manure (20 tonnes/ha), 36.5% more in digested sludge (20 tonnes/ha) and 22.6% more in combined use both the organic manures (10 tonnes/ha each). The total carotenoids were significantly higher under combined use of organic amendments and seedling inoculation in either Azotobacter or in phosphate solubilizing microorganisms. Dietary fiber content was markedly increased with use of farmyard manure (20 tonnes/ha).
  • Article
    This study had the objective to analyze the composition and the somatic cell count (SCC) of milk in farms managed by conventional and agro-ecological systems of production, localized in Depressão Central, Rio Grande do Sul State, south region of Brazil. Three agro-ecological farms were identified in the region and were compared with five conventional farms. Samples of milk were taken in the autumn-winter and spring-summer periods and analyzed for protein, fat, lactose, total solids and SCC. Milk yields and contents of fat and protein in the milk were higher in the conventional system, while lactose was higher and SSC lower, in the agro-ecological system. The main difference between the farms was the use of organic manure on the grassland, a greater number of grazing paddocks, higher level of concentrate feeding, less time spent in in the pens where roughages were fed, and use of homeopathic and phytoterapic products for control of mastitis and parasites, in the agro-ecological compared with conventional farms.