Articoli scientifici
13/07/2026

Mortality in agriculture workers: a case-control study in Italy

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Introduction

Working in agriculture includes different job activities such as cultivation, harvesting crops, rearing animals, and forestry. Among the different occupational or environmental risk factors, pesticides are the most important agents. Additional agents are solar radiation, engine exhausts, solvents, dusts, and zoonotic microbes. Pesticides are a broad category, which include insecticides, fungicides, herbicides, plant growth regulators, and other functional categories, with different levels of toxicity determined by the active ingredients and other agents in the composition of commercial products. The health effects due to their exposure are well known in literature. The main studied health effect is cancer. Reviews and individual cohort showed that farmers have a lower risk of most major causes of death than the general population particularly in terms of total mortality, total cancer, heart diseases, and specific cancers like lung cancer.1-3 According to Blair et al.,1,2 the lower risk of smoke-related cancers is consistent with the lower prevalence of smoking among farmers than among the general population and many other occupational groups, as well as to physical activities, better food, and healthier life. However, according to cohort and case-control studies,4,5 this occupational group has a higher risk of certain types of cancers such as soft tissue sarcomas (STSs), non-Hodgkin lymphomas (NHLs),6-9 Hodgkin’s disease (HD), leukaemia, multiple myeloma (MM),10 prostate cancer,11-14 and cancer of the skin and lip1,2.   
In Italy, several multicentre case-control studies have investigated the association between agricultural work, pesticides exposure and risk of cancer,6,7,10,15-19 including licensed workers20-22.
The potential of pesticides as human carcinogens has been recognized by international agencies.23,24 However, not all studies agreed on the association among agricultural work and cancer-specific outcomes, depending on the type of study, study area, workers involved, job-related activities, gender- or age-based differences, available exposure data, and working histories. While some studies have suggested associations between pesticide exposure and certain cancers, such as brain cancer,25-27 others have found no such links28-30.
Recent and past literature report that exposure to agriculture agents, like pesticides, has also been associated with neurodegenerative diseases.27,28-37 Parkinson’s disease, amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease are the most common neurodegenerative disorders, that have been related with exposure to pesticide.38-40 More recent studies involved other health effects such as epilepsy,34 tremor,35 and neurobehavioral, neuromotor, and neurocognitive effects36. Not all studies agreed on the association between agricultural work and increased risk of brain disease.31,41,42 Misclassification and inadequate response rates are considered as possible explanations for the non-association observed in some studies.43,44 
There is a lack of a comprehensive assessment of occupational risks in agriculture, as most studies focus on specific regions of a country with a limited population enrolled, primarily in cohort studies. Neurodevelopmental disorders and diseases of the nervous system other than Parkinson’s disease need further investigation. 
This study aims to contribute to the scientific knowledge on the neoplastic and neurological effects associated with agricultural work by using a case-control study design, based on national registered mortality data in the period 2005-2018 integrated with working histories derived from the National Social Insurance archive.

Methods

Study design

This study applied a case-control design based on countrywide mortality data covering the period 2005-2018.45 Blue-collar individuals with low/middle education were included in the study. Cases were selected among who died for mental or neurodevelopmental disorders, nervous diseases or for malignant neoplasms. People who died for all other causes of death different from the one under study have been selected as controls. Each case or control has been assigned to the economic sector where the individual worked for the longest period. The definition of “exposed workers” is people who had worked in the agricultural sector; unexposed workers are those who were employed in the service sector, which was assumed to be at a lower risk of pesticide exposure and to be representative of the general unexposed population.

Mortality data

Mortality data, coded according to the International Classification of Diseases – Tenth revision (ICD-10), were retrieved from the Italian National Statistics Institute (Istat) in the years 2005-2018. 
The selected causes of death with an aetiological hypothesis linked to the exposure of harmful agriculture substances as reported in scientific literature were: •â€¯mental, behavioural and neurodevelopmental disorders (F01-F99) as a group and for a specific disease like dementia; •â€¯diseases of the nervous system (G00-G99) as a group and for specific diseases like Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, and epilepsy; •â€¯malignant neoplasms of lymphoid, hematopoietic, and related tissue (C81-C96) as a group and for specific diseases like Hodgkin lymphoma, multiple myeloma, leukaemia; •â€¯others specific malignant neoplasms belonging to groups of lip, oral cavity, pharynx, digestive organs, respiratory and intrathoracic organs, skin, mesothelial and soft tissue, breast, female genital organs, prostate, urinary tract, and brain and other parts of the central nervous system (C00-C72). 
Mortality data included information on: •â€¯gender; age of death, classified in 15 classes (<19, 20-84 in 5 years and 85+); •â€¯educational level, available in 5 classes in which individuals were selected if they had lowest or no education (primary school) or middle/secondary school; •â€¯date and location of death.

Occupational data

Information on working history retrieved from the National Social Insurance Agency (INPS) was used. Data consists of employment periods from 1974 onwards spent by the worker in each private sector in his/her working life.45 The data cover about 55% of the Italian workforce and do not include data on public employment, self-employment, artisans, domestic workers, para-subordinate workers, and occasional workers. The latter represents a consistent part of the whole national workforce. As the workers involved in this study are part of the private sectors, which is fully covered by the INPS archive, the representativeness of selected individuals is fulfilled. Information about occupations was not available except for a blue-collar indication. 
Economic sectors in INPS files are classified according to the Statistical Classification of Economic Activities of 1981. Economic activities were recorded according to the Statistical Classification of Economic Activities in the European Community (NACE Rev. 2), grouped into broader categories data46 for a total of 48 sectors of employment. Among them, deceased workers employed in the agricultural and in the service sectors were selected. The latter are used as reference sector and include wholesale and retail trade, accommodation and food service activities, financial and insurance activities, administrative and support service activities. 
To maximize exposure contrasts and reduce misclassification in the assignment of the working sector, a few data selection procedures were carried out. First, for both cases and controls, blue-collar workers with low educational level (primary or middle school) were selected, because they are more likely to have been engaged in jobs and tasks entailing exposure to various agents in agriculture. Second, the median value of the years of employment for each economical sector was calculated and only those individuals with a duration of employment higher than that value (“permanence” criterion) were selected. Third, in order to avoid that multiple individual sectors of employment could confound the relationship between the cause of death and the specific sector, individuals in which the length of employment in a specific sector was prevalent (defined as the sector with at least 75% of the total years of registered working activities) were selected. 
In summary, only jobs for cases and controls with a blue-collar definition, low educated, and with sufficient (permanence criteria) and prevalent length of employment in a specific sector were included in the analysis. 

Statistical analyses

Logistic regression models were fitted to calculate mortality odds ratios and 95% confidence intervals (95%CI) for various causes of death. Occupational exposure was modelled considering the agriculture workers as exposed and the services workers as unexposed (reference). Individuals never employed in agriculture or in service sectors were, therefore, excluded. Models were adjusted for age class, gender, educational level, year of death, and region of residence; the latter was included to consider the heterogeneities of cultivations in the national territory. Analyses were also performed by gender and length of employment in agriculture (0-29; 30+ years). 
A sensitivity analysis was carried out to assess the robustness of the findings with respect to an alternative reference group of workers such as all non-agricultural sectors. For the latter, the main analysis was repeated using all other sectors (excluding agriculture) as a reference. 

Results

Among the 1.6 million workers who died during the years 2005-2018, about 1.2 million blue-collar workers with low or middle education, with sufficient permanence, and prevalent length of employment in one of 48 sectors included in the study were selected. Of these, about 64,000 and 107,000 worked in agriculture or in service sector, respectively. Most individuals who worked in agriculture were men (75%) with a primary school diploma (85%) and who started working at a median age of 39 and continued to work for a median duration of 31 years (Table 1). The unexposed group (workers in the service sector) were balanced in terms of gender (52% vs 48%), but with higher age at first employment (46 as median value) and shorter length of employment (6 years as median value) than those who worked in the agriculture sector (Table 1). 

 

 

Most of the workers were employed in agriculture from 1974 to 2004 (table S1, online supplementary materials). 
Table 2 shows MORs results for mental, behavioural, and neurodevelopmental disorders and nervous system diseases. As a group, negative associations were found between working in agriculture and mental, behavioural, and neurodevelopmental disorders. As for specific nervous system diseases, positive associations were found between employment in agriculture and spinal muscular atrophy (SMA) and Parkinson’s diseases (in men only). On overall, multiple sclerosis disease was found negatively associated with working in agriculture. The stratified analysis by length of employment carried out for Parkinson’s and SMA diseases shows a higher risk for durations lower than 30 years.

 

The group of malignant neoplasms of lymphoid, hematopoietic and related tissue was in excess in those ever employed in the agricultural sector (Table 3). It results in both genders also, with stronger association in men. Within this group, in both genders it was found an excess risk of multiple myeloma, while lymphoid and myeloid leukaemias were found associated with men only. 

 

Positive associations were found between employment in agriculture and mortality from several other cancers, including cancer of lip, stomach, skin melanoma, colon rectum, connective and soft tissue, prostate, kidney, brain and central nervous system (Table 4). 

 

Some elevated risks emerged only in men (lip cancer, melanoma of skin, malignant neoplasm of connective and soft tissue, and of brain and central nervous system). Cancer of stomach, colon rectum, and kidney were positively associated with work in agriculture in both genders, although with MORs of different magnitude. Negative associations were also found between working in agriculture and malignant neoplasms of liver and lung in both genders, of larynx and bladder in men only, of ovary in women. Neoplasm of pharynx was borderline for negative associations in the overall analysis.
For malignant neoplasms of brain, skin, stomach, colon rectum, kidney, and prostate, as well as lymphoid leukaemia, an increase of risk was observed with length of employment (table S2, online supplementary materials). Conversely, a decrease of risk with the length of employment for multiple myeloma and myeloid leukaemia was estimated.
Sensitivity analyses results about the choice of the reference group of workers show some attenuation of effect estimates, although the overall pattern of associations remained consistent (table S3, online supplementary materials).

Discussion

In this nationwide study, agricultural work was found to be associated with mortality from several diseases, including mental, behavioural, and neurodevelopmental disorders, nervous system; neoplasms of lymphoid, hematopoietic and related tissue; and specific cancers in some organs. 
Pesticides, which include insecticides, herbicides, fungicides, nematocides, rodenticides, and other preparations, are considered the main agent of exposure for agricultural workers for which there is a higher concern for occupational health.24  
The results of this study are mostly in line with the International Labour Organization’s list of occupational diseases caused by pesticides exposure, and with the past and recent literature in this field.1-3,13,14,25,27,31-37,47,48 

Comparison with literature: diseases of the nervous system

As for the diseases of the nervous system, male workers in agriculture were found to be at risk for Parkinson’s diseases, without a clear relationship with the length of employment. The evidence of the association between working in agriculture and Parkinson’s diseases is large, but also controversial. In a review by Nandipati and Litvan,33 the authors concluded that rotenone, paraquat, and organochlorines have been well-documented in human epidemiological studies to be associated with Parkinson’s diseases, while organophosphates, pyrethroids, and polychlorinated biphenyls require further studies. In a more recent systematic review, Sturm et al.31 examined 22 studies about the relationship between agricultural work and Parkinson’s disease or Parkinsonism, but they partially agree on the presence of an association. Positive associations were found in studies carried out in France,37 Norway,49 US,50 and Spain32. In Italy, one study concerning farming and Parkinson’s disease found no association.43 Positive association was instead found in a case-control study in North-Eastern Italy.51 Other authors show that genetic factors may act as effect modifiers.52-54 
The present study found an association between working in agriculture and mortality for the group of spinal muscular atrophy diseases in both genders. The risk seems not to depend on the length of employment, with individuals having duration lower than 30 years more at risk than those with higher length of employment. A few studies found an association between pesticide exposure and the development of ALS, a disease part of SMA group.55-57 In Italy, there is poor information about this disease in connection with working in agriculture. Filippini et al.,58 in a population-based case-control study in four Italian provinces, found no statistically significant positive association with ALS risk in agricultural workers. The results of the present study are in line with scientific literature and add further evidence to this field of study. This study found multiple sclerosis disease negatively associated with working in agriculture. Studies providing some indication about the relationship between environmental exposure to pesticides and multiple sclerosis disease incidence are few, fragmentary, and discordant.59 Consequently, further investigations are needed. 
No association was found with mortality for Alzheimer’s disease and epilepsy, although these health effects were positively associated with exposure to pesticides in Spain32,34 and in a review by Gangemi et al.55. At the same time, working in agriculture was found to be negatively associated with multiple sclerosis and with the group of mental, behavioural, and neurodevelopmental disorders, as well as a signal of negative association with vascular and unspecified dementia.

Comparison with literature: cancer

As for cancer effects caused by long-term exposure to agents in agricultural workers, some studies have suggested an association between pesticide exposure and Hodgkin’s disease, leukaemia, non-Hodgkin lymphoma, multiple myeloma1,2,6-10 as well as tumours of the lip, stomach, prostate, skin, brain, and connective tissues1,2,27,31. The International Agency for Research on Cancer (IARC), evaluating the cancer risk associated with non-arsenical insecticide spraying, has concluded that this activity is probably carcinogenic to humans (Group 2A) and recently some active ingredients have been evaluated as certain or probable carcinogens for humans,23,60 likely causing an increased risk for skin, lymphatic, and lung cancer. However, no pesticide has sufficient evidence in humans to be classified as a brain or central nervous system carcinogen by IARC.23,61 
The results of the present study confirm the above evidence of cancer effects related to agricultural workers, providing evidence of risk for specific cancer types. These risks were not clearly dependent on the length of employment. While neoplasms of brain, skin, stomach, colon rectum, kidney, and prostate show a higher risk for durations higher than 30 years, others like lip and ovary neoplasms show opposite behaviour. In agreement with early studies by Blair et al.1,2 and Italian case control ones21,62,63, this study confirms no risk for some smoke-related cancers like lung, bladder, larynx, and liver, likely due to the lower prevalence of smoking as well as a higher level of physical activity among farmers than the general population and other occupational groups. However, the protective risk estimates observed in agricultural workers must be interpreted with caution. It could be partly attributable to a healthy worker effect. It could reflect protective lifestyle or environmental factors or could be affected by biases such as information bias, given the heterogeneous nature of agricultural exposures. The risk of prostate cancer in agriculture workers was found to be twice that of those of services, a value which is higher compared with existing literature. Pesticide and endocrine exposure might be one of the factors that may be involved in the observed result, as well as the specific case-control study design used which is known to produce higher risks estimates.64
As for brain cancer, the results of this study are in line with a study about mortality in male farmers licensed to use pesticides,20 with an Italian case-control study on farmer work and the cancer morbidity65, and with some recent reviews27,31. The present study provides additional information about its prevalence in men workers and in farmers who worked for more than 30 years. 
This study confirmed results of the Italian case-controls studies about the increase of risk for lymphoid, hematopoietic and related tissue cancer group,15 and some specific chemical classes of pesticides17,19. Within this group, multiple myeloma, lymphoid, and myeloid leukaemia were found positively associated with working in agriculture. Conversely, an early mortality study about farmers in central Italy found no association with NHL, Hodgkin’s lymphoma, multiple myeloma, and leukaemia.66 For most of the diseases in this group, a stronger risk was found in individuals with less than 30 years of employment, out of the risk of lymphoid leukaemia, which shows opposite behaviour. A recent multi-centre case-control study carried out in Italy found a 7-fold risk of follicular lymphoma (FL) in subjects classified as ever exposed to glyphosate, but no association with risk of lymphoma (any subtype), NHL, B-cell lymphoma, or the major lymphoma subtypes other than FL.67 Evidence from recent studies (meta-analyses and large cohort studies) indicates a modest but consistent increased risk of hematopoietic malignancies among agricultural workers, with stronger associations for non-Hodgkin lymphoma and multiple myeloma, suggesting a potential role of occupational exposure to pesticides particularly insecticides, herbicides, and fungicides.68-70 An elevated multiple myeloma risk was observed among farmers with long-term pesticide use on crops and animals, particularly corn treatments and insecticide use in horse farming in the 1960s and disinfectant use in animal barns.71 Hodgkin lymphoma was also associated with pesticide exposure, although the low statistical power, a mixture of histological subtypes, and a lack of information on tumour Epstein-Barr virus (EBV) status complicate the interpretability of the results.72

Strengths and limitations of the study

The main strength of this study is the large sample size drawn from a nationwide population over an extended period. Furthermore, the use of administrative data avoids possible recall biases that might have affected previous case-control studies results. Moreover, the adopted selection criteria maximize exposure contrasts (long absolute and relative employment in agriculture; blue-collar workers with primary/middle education).
On the other hand, several limitations must be considered. 
First, this study is based on mortality data, which reflect both disease incidence and survival; therefore, it is not optimal for investigating diseases with low lethality. Consequently, there is the possibility that mortality differentials reflect healthcare access or survival differences rather than incidence. 
Second, it is based on the assumption that dead controls adequately represent the exposure prevalence in the study-base (the population-time from which cases emerged). Although theory state that controls deaths should be chosen among those unrelated to the exposure of interest,73 including all other diseases is regarded as a reliable approach, because “there are few factors that markedly increase risk of numerous diverse diseases”;74 in other words, if the control series contains one or more diseases associated with the exposure, their effect would be “diluted” by the other diseases unrelated with the exposure. 
Third, there are several potential sources of bias. A possible source of bias concerns the selection mechanisms related to the inclusion criteria: to strengthen the causal link between employment in a given sector and death from a specific cause, the study population was restricted to individuals with well-defined occupational characteristics, as described above. This approach reduces misclassification and enhances representativeness of the target population (i.e., agricultural workers with sufficient employment duration). In addition, the use of a crude classification of exposure – defined dichotomously as exposed or unexposed based on the sector of employment – represents another potential source of bias. This approach may introduce non-differential misclassification, which would likely bias the estimates towards the null.
Fourth, occupational administrative data cannot adequately characterize occupational exposure profiles. INPS data report the industrial sector, but do not provide information on workers’ occupations. The complexity of exposure patterns, the difficulty in reconstructing past exposure, considering the change over time in specific chemical use, and the variation in work practices should be considered. Consequently, occupation data used in the present study consists only of the working-time spent in specific sectors, without an individual exposure assessment. In this study, a marked difference was observed in the duration of employment between exposed individuals (agricultural workers) and unexposed individuals (service workers). The longer employment duration among agricultural workers is likely attributable to sector-specific characteristics. In this sector, it is customary to continue paying social security contributions even at an advanced age in order to retain access to benefits and maintain the availability of cultivated land. No evidence was found to suggest that individuals with extended contribution periods are merely nominally active in the sector while being effectively unexposed. In contrast, the service sector shows contribution periods that are consistent with those observed in other sectors. Additionally, for both exposed and unexposed workers, the possibility that other occupational activities not recorded in the INPS archive may have been carried out during their working life, potentially resulting in additional undocumented exposure, cannot be excluded.
Furthermore, potential important factors were not considered; among them: specific job-related activities, heterogeneity of agricultural work itself (e.g., crop type, animal type), type of pesticide applied, synergies between risk factors, and actual dose of exposure. Consequently, this study suffers from non-differential misclassification, which on average biases MORs towards to the null. Lack of information on potential confounders (e.g., socioeconomic and lifestyles factors) should be considered for several cancers. 
As smoking is a factor related to numerous health outcomes, including cardiovascular and respiratory diseases, and was included in this study among the causes of death for controls, Authors acknowledge the possibility of a potential bias in the study findings. To assess this issue, a sensitivity analysis was conducted excluding smoking-related diseases from the causes of death among controls. The results indicated non-significant variations in the estimated MORs, thereby supporting the robustness of the approach. These findings are consistent with previous studies,73,74 which have suggested that, if the control series includes one or more diseases associated with the exposure, their effect may be diluted, often leading to a null association.
Finally, as multiple comparisons were conducted across many outcomes, the risk of type I error is acknowledged. However, no focus was made on statistical significance strictly, but the considered approach was based on the previous literature findings and plausibility.

Conclusions

The findings of the present study suggest that working in agriculture is associated with several health risks, including neurological diseases and cancers of lymphoid, hematopoietic and related tissue as well as cancers of brain and central nervous system. Additional excess risks for prostate, kidney, stomach, and colon rectum cancers were observed with gender differences. These effects may be associated with occupational and environmental exposure to pesticides and other agents encountered in this sector. Although their use has been quantitative and qualitative regulated over the years, their health effects remain a concern due to their extensive past use. The findings of this study demand for further targeted prevention measures, especially for classes of compounds for which specific risks for human health have been identified. Elevated risks of skin cancers were also found, for which sun and ultraviolet radiation exposure are a well-recognized risk factor. 

Conflicts of interest: none declared.

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