There
is now scientific consensus that pesticides cause cancer among farmers.
This conclusion has been confirmed by the courts insofar as one type of
cancer, non-Hodgkin’s lymphoma, has been classified in France as a
professional disease affecting farmers due to exposure to pesticides.
How many farmers have fallen victim to this disease? Surprisingly INSERM
(French National Institute of Health and Medical Research), when
recently approached by a French inter-ministerial mission, stated that
it was unable to quantify the number[1].
How is it that we are still at this stage for a disease whose link with
agricultural workers is so well documented? To get some perspective on
this, we need to look back on the history of research on farmers’ health
… and how it has progressively lost traction!
Concerns stemming from retrospective case-control studies
Research into the long-term effects of pesticides on farmers took off
in the 1970s as people became more aware of the effects of the
accumulation of these substances in the environment. This was especially
true for organochlorine pesticides. Since this was an after-the-fact
analysis of the impact of products that had already been in use for a
long period of time, the first epidemiological research consisted of
retrospective case-control studies.[2]
This type of survey is known to be potentially susceptible to many
biases but since it provides quick results it is typically used at the
early stages to identify a new health problem.
These early case-control studies quickly revealed that farmers were
overrepresented among the victims of a fairly large number of
pathologies, mainly cancers and neurovegetative disorders.
Unfortunately, these retrospective studies do not allow for an accurate
calculation of the number of cases over the mean in exposed populations.
Moreover, it is no easy task to reconstruct the list of products to
which the farmers studied were exposed, in some cases a long time ago.
Prospective cohorts: reassuring results
These initial disturbing results sparked a number of cohorts, i.e.
studies of the health events affecting large populations of farmers
still in good health and the monitoring of their use of pesticides.
These cohorts are the basis for the so-called prospective studies which
are much more expensive than their retrospective counterparts because
they require the collection of massive amounts of information and take
more than 10 years to start producing significant results. But they are
much more reliable and only they can calculate incidence rates (number
of new cases each year) and mortality rates (number of deaths caused
each year) among farmers and compare these figures to those of the
general population. The two largest cohorts on this topic are:
- The 1993 AHS (Agricultural Health Study) cohort in the USA monitoring the health of approximately 90,000 farmers (pesticide operators and their wives)
- The larger 2005 Agrican cohort in France monitoring approximately 180,000 people, a very significant sample of the French agricultural population. Moreover, the Agrican cohort also includes a significant proportion of farmers who do not use pesticides which could lead to the study of potentially confusing factors, i.e. health risk factors other than pesticides but which are also associated with agricultural work).
These prospective cohorts finally made it possible to calculate the
standardized incidence of disease and mortality for farmers in
comparison with these same figures for the general population. These
studies should therefore allow researchers to identify the number of
excess cases among farmers in comparison with the general population.
For example, a standardized incidence of 1.10 among farmers means that
there were 10% more new cases of the disease in that group in comparison
to the number of cases affecting the general population. The results of
the two cohorts are very consistent … and should be reassuring judging
by the traditional interpretation of standardized incidence ratios and
standardized mortality ratios :
Table 1: Standardized incidence and mortality ratios for different forms of cancer in Agrican (F) and AHS (USA) cohorts. References: Incidence:
Koutros et al. / J Occup Environ Med. 2010 November; 52(11): 1098–1105
(pesticide operators; 1st figure: Iowa; 2nd figure: North Carolina) C.
Lemarchand et al. / Cancer Epidemiology 49 (2017) 175–185 (men using
pesticides) Mortality: Waggoner et al., Am J Epidemiol 2011;173:71–83
(men using pesticides) Lévêque-Morlais et al. 2014 : Int Arch Occup
Environ Health DOI 10.1007/s00420-014-0933-x
Standardized mortality of farmers is not above normal for any form of
cancer. In fact, their mortality is significantly lower than that of
the general population for most types of tumors while mortality is
average for the rest.
Concerning the incidence of cancer, the global results for farmers
are not quite as good as for mortality but are still very reassuring
overall. The incidence in farmers is significantly higher for only three
types of cancer: Lip and prostate cancer and multiple myeloma. We will
focus on these three particular cases in a future article but for now
let’s start with a snapshot of the global results: for about 1/3 of the
cancers studied (mainly cancers of the respiratory and digestive tracts
and the bladder), the standardized incidence of cancer in farmers using
pesticides is significantly lower than the mean; for nearly 2/3 of the
other types of cancer, there is no significant difference with the
general population. Moreover, these non-significant results are
typically less than 1 and feature relatively narrow confidence intervals
making it unlikely that they hide many effects of pesticides that may
have slipped through the statistical “filter”. The similarity of the
Agrican and AHS studies give even greater credence to the results.
The results of these cohort studies, designed to confirm or
contradict the results of the case-control studies, should therefore be
considered reassuring. If one adheres to the usual interpretation of
standardized incidence and mortality, there are only three forms of
cancer that affect farmers significantly more than the general
population and this difference is only for incidence and not mortality.
The “healthy worker effect”: a statistical truth or a pretext?
Surprisingly (or not), these results have not received much attention
in official bibliographic reviews or meta-analyses such as the
collective expertise of INSERM 2013, and no clear reason for these
reservations has been offered. In fact, it was the aforementioned
interdepartmental mission on compensation for pesticides[3] which
led INSERM to give the most transparent explanation for its reluctance:
the lifestyle of farmers is associated with a number of factors
protecting them from cancer. They smoke less than the general population
and often have a more balanced diet, which could explain their low
incidence of respiratory and digestive tract cancer. We also see a
“healthy worker” effect in other occupations involving regular physical
exercise often making these professionals healthier than the average.
Consequently, INSERM warns that these favorable effects may conceal or
mask the negative effects of pesticides. In other words, some
pesticide-related cancers may go unnoticed when comparing farmers to the
general population as the healthier lifestyle of farmers could offset
this effect. This is why INSERM warns against an overly “simplistic” use
of standardized incidence where normal incidence would indicate that
pesticides do not have any impact.
This reluctance on the part of epidemiologists is perfectly
understandable but this would mean that the standardized incidence and
mortality which they continue to calculate in their publications are not
valid indicators. It is therefore somewhat surprising that this problem
has not yet been addressed considering that the first works on
prospective cohorts date back some ten years. It is common practice in
other areas to correct incidence based on the consumption of tobacco or
alcohol and a number of studies on farmers have done just that. The most
general objection based on the “healthy worker” effect could be
mitigated by developing standardized incidence figures where the
reference population would no longer be the population at large but
rather the general labour force. However, to date INSERM has not made
any proposals in this regard.
We would further note that the consequence of INSERM’s reasoning
should be verifiable in the Agrican cohort. In other words, if for some
cancers there is a “healthy worker” effect that masks the adverse effect
of pesticides, it stands to reason that the incidence of cancer in
farmers who do not use pesticides should be lower than that of their
pesticide using counterparts. Indeed, the often mentioned “healthy
worker effect” should be visible among both groups of farmers (non-users
and conventional), the health of the non-users not being diminished by
the adverse effect of pesticides. However, the most recent figures
provided by Agrican on the incidence of cancer[4] do not reflect this effect at all. In fact, they show the opposite trend[5]!
Fig 1: Standardized incidence of cancer (all types) among farmers
and agricultural workers in the Agrican cohort, based on their use of
pesticides (“users of other pesticides” are those who have used only
veterinary products or pesticides to maintain uncultivated areas). The
dots represent mean value while the vertical lines show the confidence
interval (95%). The authors did not carry out a statistical analysis to
check whether the differences between these three populations are
significant, but we would note that the 95% confidence intervals
(vertical lines) for users and non-users of pesticides do not overlap.
It is therefore likely that this difference is significant … but to the
detriment of the non-users of pesticides who actually suffer more cases
of cancer!
Admittedly, a closer look at the different types of cancer indicates
that the confidence intervals found for farmers who do not use
pesticides are too high to draw reliable conclusions. But in any case,
there is currently no evidence to statistically support the hypothesis
that the factors protecting farmers from cancer are strong enough to
mask the allegedly harmful effects of pesticides.
The rush towards irrefutability
Epidemiologists have therefore rejected the use of standardized
incidence and mortality to determine whether or not pesticides cause
cancer among farmers. However, the veracity of their reasonable
objection (the “healthy worker” effect) has yet to be proven. Instead of
trying to statistically prove the existence of the “healthy worker”
effect by comparing users and non-users of pesticides to the general
labor force, recent studies have opted to compare groups of farmers
based on the crops they grow. Several recent publications on the Agrican
cohort highlight significant differences in the incidence of some
cancers based on the crops produced or animals raised on the farm. Since
pesticides are generally only used on a fairly narrow range of crops,
these results are generally interpreted as indicators of the specific
pesticides responsible for an excessive number of cancer cases. This is
no doubt an interesting approach but there are still two rather
troublesome gaps characterizing these studies:
- They no longer provide a comparison with the general population. For example, it is interesting to point out that there are significantly more cases of prostate cancer among grassland farmers than among their non-grassland counterparts as a recent Agrican publication has shown[6]. But this still does not tell us whether grassland farmers suffer more from prostate cancer than the general population.
- These comparisons between agricultural production systems distinguish among a fairly large number of crops and/or animal species. In the example just cited, the authors distinguished the incidence of prostate cancer associated with 13 different crops. Analyses such as these are typically affected by the well-known “multiple comparison” effect, i.e. the risk of obtaining a statistically significant result that is simply due to chance when one conducts a large number of statistical tests. In the case of these 13 comparisons, an elementary probability calculation shows that this risk stands at 49% (1-0.9513)[7]. Results such as these should not be considered as a serious alert unless one of the following two conditions is met:
- either its seriousness is confirmed by an additional statistical test to eliminate the “multiple comparison” effect (Bonferroni test or FDR approach), and neither of these tests were performed in this study,
- or we observe the same type of result for the same crop and the same cancer in another cohort. To our knowledge, this link between prostate cancer and grassland farming has not been observed anywhere else. Moreover, in the Agrican cohort it is associated with an excess of prostate cancer among cattle farmers (for an obvious reason: they are more likely than other farmers to farm grasslands). However, the American AHS cohort shows no significant link between cattle farming and prostate cancer[i].
In studies such as this which compare risks based on the crop grown,
significant results may be acquired but these may be due to chance and
are never confirmed. They do, however, maintain suspicion on some
harmful effect of the pesticides even though it is not known whether the
excess number of cases observed for certain crops is due to a risk
higher than that of the general population. The field of possible
effects of pesticides has therefore become more and more restricted to a
few types of cancer and certain crops based on scientific arguments
that are increasingly ambiguous.
From scientific hypothesis to irrefutable consensus
As we have seen in this brief history of epidemiological studies, the
plausibility of the possible effects of pesticides on cancer in farmers
has declined steadily over time.
- The initial case-control studies suggested perceptible adverse effects for all farmers for approximately a dozen types of cancer.
- Prospective cohorts only indicate serious (but not completely consistent) evidence for three types of cancer: lip and prostate cancer and multiple myeloma. However, as we will see in a future article, recent studies on these three cancers shed very little light on the existing uncertainties, i.e. explanation for the discrepancy between incidence and mortality rates, or causes for the above average number of cases also observed in farmers who do not use pesticides.
- The current trend is to draw comparisons between subpopulations of farmers which are supposed to demonstrate the risk of pesticides associated with the crops they grow. However, the methods they use are increasingly questionable from a statistical point of view and make no comparisons with the general population.
The fact is that the amount of evidence required to suggest a
carcinogenic effect of pesticides has declined steadily. Results
suggesting the safety profile of pesticides (credible insofar as they
confirm the validity of approval procedures) are systematically rejected
and with admittedly plausible objections but ones that epidemiologists
never manage to validate.
- Standardized incidence rates which are normal or even less than 1 are discarded because they may be biased by a mysterious “healthy worker” effect regularly invoked by epidemiologists who never try to correct or even measure these admittedly plausible effects.
- The fact that there was no difference between farmers who use and those that do not use pesticides was either never addressed or was interpreted as demonstrating “contamination” of the pesticide-free group, but once again without any proof (see next article).
This change in discourse reflects the shift in the epistemological
status of the hypothesis of a carcinogenic effect of pesticides in
farmers. In other words, it has progressively morphed from scientific
work hypothesis status to that of irrefutable consensus. However,
although counterintuitive, the term irrefutable is not at all
flattering. Since the work of K. Popper, it is believed that the main
difference between true science and pseudo-science is its refutability: a
truly scientific hypothesis is a one for which one can imagine an
experience that refutes it. The initial hypothesis that pesticides cause
cancer in farmers is indeed a scientific hypothesis. In other words, it
can be refuted (or validated) by measuring the incidence of cancer
among farmers who use pesticides and comparing that to the rest of the
population. But we have seen that this hypothesis has tended more
towards refutation. The new hypothesis which claims that the harmful
effect of pesticides may be masked by a so-called “healthy worker”
effect is also a scientific hypothesis, i.e. it can be refuted (or
validated) in two ways:
- by comparing the incidence of cancer in farmers to that of other occupations involving moderate physical activity;
- or by comparing the incidence of cancer in farmers using pesticides and farmers not using any.
Since neither of these comparisons has been made to date, the refutability of this hypothesis remains entirely theoretical.
If farmer cohort studies are to regain true scientific status, it is
high time that epidemiologists define what criteria they would be
prepared to accept as indicating that the incidence or mortality of a
type of cancer in farmers is normal. This is all the more necessary
since the precautionary principle requires defining the criteria
according to which a technology can be considered harmless. This is
precisely the work of the health agencies. They are the ones responsible
for declaring, based on experimental results, that a product can be
considered as non-hazardous. If researchers fail to decide on a set of
rules allowing them to take that same decision (which is understandable
after all as that is really not their job), it is incumbent upon the
agencies, based on the work done by experts on the results of
epidemiological studies, to draw clear and operational conclusions
rather than allowing suspicion and non validated hypotheses to linger on
indefinitely.
Furthermore, INSERM publications on the Agrican cohort fall prey to
the major pitfall affecting the research community: focus on
statistically significant results[8].
No additional analysis is conducted on the mass of non-significant
results (except meta-analyses to try to make them significant …) even
though the notion of “non-significant” result actually covers two very
different realities:
- results that are truly “non-significant” because their excessive confidence interval precludes any possibility of interpretation;
- and “quasi-significant” results whose critical probability (probability that they are due to chance) is just barely over 5% and whose evidential value is therefore just below that of the ones receiving the sacred seal of “statistically significant”.
Fig 2: Examples of standardized incidence obtained for 3 forms of
cancer in the most recent assessment of the Agrican cohort for farmers
who use pesticides. The dots represent mean value while the
vertical lines show the confidence interval (95%). In scientific
publications, analysis focuses on significant results (whose confidence
interval does not cross the value of 1 in red), especially if they are
greater than 1 because they are the ones that indicate a link between
exposure to pesticides and cancer. Very little attention is paid to
non-significant results even though their value differs according to the
sanitary expertise conducted. In the example given, it is impossible to
conclude anything about the incidence of liver cancer because the width
of its confidence interval is much greater than its deviation from 1.
On the other hand, the result concerning rectal cancer, although
non-significant as well, is much more relevant in sanitary expertise
because the value of 1 is very close to the upper limit of its
confidence interval. A simple complementary analysis would suffice to
calculate the probability of an excessive number of rectal cancer cases,
but it is obvious that this probability is only slightly higher than 5%
(the typical significance level). Sanitary expertise needs this type of
analysis highlighting the importance of non-significant results to
prioritize research but researchers are not providing it.
The distinction between these two types of results will be important
in guiding future research. Regarding the example illustrated in Figure
2, it is likely that uncertainty will continue to decrease regarding the
results of rectal cancer as the cohort study continues to be monitored,
until it reaches a level where it can be concluded, without much risk
of error, that this form of cancer does not present any particular
hazard. In contrast, for liver cancer the number of cases currently
observed is too low and as a result the uncertainty range is so wide
that it is unlikely that clearer results will be obtained in the future
from the Agrican cohort alone. Therefore, it will become vital to
analyze the statistical power of Agrican’s non-significant results
despite the fact that this is not common practice in research (but is
perfectly acceptable for health agencies).
While waiting for ANSES (The French Health Agency for Food Security)
to eventually take a firm stand, we are witnessing this strange paradox:
with Agrican, France has the largest prospective cohort of farmers in
the world, but its decisions on the recognition of occupational diseases
utterly fail to take the results of this cohort into account. None of
the only three types of cancer for which Agrican provides warning signs
is currently classified as a professional hazard. In contrast,
non-Hodgkin’s lymphoma is included in the tables of occupational
diseases even though Agrican provides no evidence for this decision.
This subject alone merits a follow-up article because it is indicative
of other scientific problems which are yet to be solved by the approach
used by epidemiologists. This article will also provide an opportunity
to examine the strength of an argument often considered decisive by
opponents of pesticides: cases of dose-response relationships between
exposure to pesticides and the risk of certain cancers.
[1] http://www.forumphyto.fr/2018/05/08/combien-de-victimes-des-pesticides-quand-linserm-se-declare-incompetent/
[2] More information about the different types of epidemiological studies, see http://www.ipubli.inserm.fr/bitstream/handle/10608/222/?sequence=31
[4]https://www.researchgate.net/publication/318371068_Cancer_incidence_in_the_AGRICAN_cohort_study_2005-2011
[6] Ref 3, Table 2
[7] https://www.google.fr/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjRrY-575LcAhWIthQKHVNJD8UQFggpMAA&url=https%3A%2F%2Fwww.academie-agriculture.fr%2Fsites%2Fdefault%2Ffiles%2Fsections%2Ffichiers-prives%2F20180530pourquoicontroverses.pdf&usg=AOvVaw1h9MFi8iiisMXX0u8gfgG6 , p 17-26
