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Predictors of early cessation of dairy farming in the French Doubs province 12-year follow-up.

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AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 55:136–142 (2012)
Predictors of Early Cessation of Dairy Farming in
the French Doubs Province: 12-Year Follow-Up
Ibrahim Njoya Mounchetrou, MD,1 Elisabeth Monnet, MD, PhD,2,3 Jean-Jacques Laplante,
Jean-Charles Dalphin, MD, PhD,5,6 and Isabelle Thaon, MD, PhD1,5
4
MD,
Background A healthy worker effect due to respiratory disability has been noted in
the farming population, but other factors may also interfere. Little has been published
about factors influencing the early cessation of work in self-employed dairy farmers.
Methods Two hundred and nineteen dairy farmers were included from a cohort constituted in eastern France in 1993–1994 with a 12-year follow-up. Spirometric data,
personal, and farm characteristics were registered. Cox models with delayed entry in
which age was the time-scale were applied to identify the baseline predictive factors
of the early cessation of dairy farming.
Results Working in a modern farm was protective against early cessation of dairy
farming (hazard ratio: 0.36 [95% CI: 0.16–0.81]), especially in men. Having asthma
was a predictive factor of early cessation, especially in women (hazard ratio: 16.12
[95% CI: 3.28–79.12]).
Conclusions The most predictive factors of early cessation of dairy farming were
health related in women and farm related in men. Am. J. Ind. Med. 55:136–142,
2012. ß 2011 Wiley Periodicals, Inc.
KEY WORDS: follow-up; healthy worker effect; dairy farming; self-employed; early
retirement
1
Service de Maladies Professionnelles, Centre Hospitalier Universitaire de Nancy,
Vandoeuvre le' s Nancy, France
2
Service d’He¤patologie et de Soins Intensifs Digestifs, Centre Hospitalier Universitaire
de Besançon, Besançon Cedex, France
3
EA 3186 Agents Pathoge' nes et Inflammation, Universite¤ de Franche Comte¤ , Besançon,
France
4
Mutualite¤ Sociale Agricole of Besançon, Besançon Cedex, France
5
UMR 6249 CNRS/Universite¤ de Franche-Comte¤, Laboratoire Chrono-environnement,
Besançon, France
6
Service de Pneumologie, Centre Hospitalier Universitaire de Besançon, Besançon,
Besançon Cedex, France
Contract grant sponsor: Re¤seau National de Sante¤ Publique (FIS) and INSERM; Contract
grant numbers: CNEP 93; CN 20;
Contract grant sponsor: SERF Group; Contract grant number: EA 2276;
Contract grant sponsor: French Ministry of National Education, Research and
Technology.
Contract grant sponsor: CNMRT (Comite¤ National de lutte contre les Maladies Respiratoires et la Tuberculose ¼ National Committee against Respiratory Diseases and
Tuberculosis).
Disclosure Statement: The authors have no conflicts of interest to declare.
*Correspondence to: Dr. IsabelleThaon, MD, PhD, Centre de Consultations de Pathologies
Professionnelles, Batiment Philippe Canton, CHU de Nancy, rue du Morvan 54511 Vandoeuvre les Nancy cedex, France. E-mail: i.thaon@chu-nancy.fr
Accepted 7 October 2011
DOI10.1002/ajim.21031. Published online 8 November 2011in Wiley Online Library
(wileyonlinelibrary.com).
ß 2011Wiley Periodicals,Inc.
INTRODUCTION
Occupational and nonoccupational respiratory diseases both have an impact on work status [Ameille
et al., 1997; Gassert et al., 1998; Alexopoulos and
Burdorf, 2001; Blanc et al., 2001; Larbanois et al., 2002;
Vandenplas et al., 2003; Thaon et al., 2008]. Healthy hire
effect, job selection and healthy worker survivor effect
have been observed in numerous respiratory morbidity
studies, particularly on asthma [Le Moual et al., 2008;
Olivieri et al., 2010] and chronic bronchitis [Radon et al.,
2002]. Farmers, in particular swine farmers and dairy
farmers, have increased risks of chronic bronchitis,
asthma, and accelerated decline in lung function [American
Thoracic Society, 1998; Dalphin et al., 1998b; Vogelzang
et al., 1999; Chaudemanche et al., 2003; Dosman et al.,
2004]. A healthy worker effect has also been already
noted in farming populations [Thelin and Hoglund, 1994;
Vogelzang et al., 1999; Braback et al., 2006]. However if
health parameters, in particular respiratory illness, may be
related to cessation of farming, other factors may also
Early Cessation and Dairy Farming
interfere: economic parameters, for example, in the selfemployed farming population.
In the Doubs, a province in eastern France, a 12-year
follow-up of respiratory health was conducted in three
dairy-farmer cohorts [Chaudemanche et al., 2003; Gainet
et al., 2007; Thaon et al., 2011]. Previously published
results showed a significant excess of respiratory symptoms, lower SpO2 and increased decline in FEV1/FVC in
farmers compared to controls [Dalphin et al., 1998a;
Chaudemanche et al., 2003]. Modernization of the farm
was also found to have a positive impact on lung function
[Venier et al., 2006].
The aim of the present study was to identify the baseline personal characteristics, lung parameters, and/or farm
characteristics that were predictive of early cessation of
dairy farming in this cohort.
137
MATERIALS AND METHODS
measured in grams per day, and subjects were classified
either as nondrinkers (intake under 10 g/day) or drinkers
(intake over 10 g/day).
The occupational questionnaire was designed in
collaboration with engineers and technicians from the
local Department of Agriculture and the Mutualité Sociale
Agricole (MSA, farmworkers’ mutual). Registered variables included the size of the farm (in hectares, 1 ha ¼
2.47 acres) and the size of the herd and the hay storage
method. In the present study farms of two categories were
used: modern or modernized and traditional. Modern
farms were defined as farms with electric ventilation of
the barn and stable (tunnel ventilation system) or farms
with barn fodder drying techniques. Modernized farms
had at the very least a central corridor, loading machines,
or a separation between house and stable. Traditional
farms had none of these elements [Dalphin et al., 1998a;
Venier et al., 2006].
Sample
Respiratory function tests
The study population was based on a cohort constituted in 1993–1994 of 265 male and female dairy farmers,
who were owner or main operator of the farm, aged 16–
66, all living in the Doubs. The design and longitudinal
follow-up of this cohort has been described previously
[Chaudemanche et al., 2003; Thaon et al., 2011].
The present study included only those farmers who
were under 59.5 years old at baseline in 1993–1994 and
who had been evaluated at least once during follow-up
(either in 1999–2000 or in 2006).
This study was approved by the Biomedical Research
Ethics of the university hospital of Besançon (France) and
by the local ethics committee. All participants signed informed consent.
Spirometric data were performed according to ATS
recommendations [Gardner, 1988] with a portable pneumotachograph [Dalphin et al., 1998a]. A minimum of
three adequate measures of forced vital capacity (FVC),
forced expiratory volume in 1 s (FEV1), forced midexpiratory flow (FEF25–75%FVC) and forced peak flow (PF)
were taken and the best blow was selected. Values were
expressed as absolute values and as percentages of European Coal and Steel Community (ECSC) reference values,
calculated for sex, age, and height [Quanjer, 1983]. We
categorized absolute FEV1/FVC ratio values in three
groups: obstructive syndrome (FEV1/FVC < 70%), mild
obstruction (70% FEV1/FVC 80%) and normal ratio
(FEV1/FVC > 80%).
Baseline Investigations
Follow-up and primary outcome
Occupational and medical
questionnaires
The same procedure used for the baseline investigation in 1993–1994 was used for re-evaluation in 1999
and 2006. The most noteworthy outcome was the early
cessation of dairy farming, defined as stopping before
59.5 years of age; retirement age for French agricultural
workers was 60 at the time of the study. The date of cessation and the reasons for stopping (retirement, respiratory
or other diseases, economic reasons, other reasons) were
recorded for subjects who had stopped dairy farming during follow-up.
Questionnaires were sent by mail 10 days before the
scheduled medical examination and were collected during
a check-up examination. The medical questionnaire was
based on the long version of the European Community
Respiratory Health Survey questionnaire [Burney et al.,
1994]. The variables included socio-demographic factors,
respiratory history, chronic and acute respiratory symptoms, smoking, and alcohol habits. Cough and phlegm
were classified as winter symptoms and categorized as: no
cough or phlegm and cough or phlegm for more or less
than 3 months a year. Smokers were defined as farmers
having smoked on average at least one cigarette, one
cigar, or one pipe a day for a year. Alcohol intake was
Statistical Analysis
Categorical variables were expressed as percentages,
and continuous variables were expressed as mean
(standard deviation).
138
Mounchetrou et al.
First, farmers included in the analysis and those lost
to follow-up were compared for baseline characteristics,
with the chi square test for categorical variables and t test
for quantitative variables.
Second, we conducted a longitudinal analysis to investigate the effect of baseline characteristics on the hazard of early cessation during follow-up. For this analysis,
subjects remained in the risk set either until they stopped
farming or until they reached their 60th birthday. The
Kaplan–Meier method was used to assess the effect of age
at inclusion on the hazard of early cessation. Because hazard increased more as a function of age than as a function
of time-on-study, we applied Cox models with delayed entry in which age was the time-scale [Korn et al., 1997;
Cheung et al., 2003], in order to test the effect of baseline
characteristics in univariate and multivariate analysis. The
significance of variables was assessed with the Wald test.
All significant variables with P < 0.20 in univariate analysis were retained for multivariate analysis and all interactions between significant variables were tested. As there
was a strong collinearity between clinical symptoms and
respiratory function tests, separate multivariate models
were built for these factors. Final models were systematically adjusted on sex and smoking status and interactions
were tested with both variables.
Hazard ratios (HR) with their 95% confidence intervals (CI) were estimated. Computations were performed
using SAS version 9.02 (SAS Institute Inc., Cary, NC).
For all statistical tests, P-values inferior or equal to 5%
were considered significant.
RESULTS
Two hundred and twenty-three of the 265 dairy farmers present in the 1993–1994 cohort were included in the
study. In the 1999–2000 follow-up, 178 farmers were evaluated. One hundred and eighty-seven farmers were evaluated in 2006, among whom only 163 had been evaluated
in 2000. Seventeen farmers lost to the 1999–2000 and
2006 follow-ups were excluded from the final analysis. Finally, 202 (90.6%) of the 223 were analyzed, of whom
190 (94.06%) of 202 had valid respiratory function tests
(Fig. 1).
At baseline, the analyzed farmers were on average
43.32 (10.09) years old, with 117 (57.90%) men and 85
(42.10%) women.
Baseline characteristics did not differ significantly between analyzed subjects and those lost to follow-up
(Table I), with the exception of farm characteristics: 9.5%
versus 29.4%, respectively (P: 0.02).
Fifty (24.8%) of the 202 farmers who stopped dairy
farming early named the following reasons for cessation:
respiratory diseases (12.8%), other diseases (19.2%), age
(31.9%), economic reasons (8.5%), or other reasons
FIGURE 1. Description of dairy farmers evaluated at each of three times of the
study.
(27.7%), for example the spouse’s retirement, leaving the
farm to children, conflict between the associates.
Risk of early cessation was strongly related to age at
inclusion: the Kaplan–Meier results showed that, at 4-year
estimation, no farmers under 39 years old had stopped
dairy farming, versus 1.5% of those 39–49 years old
and 36.7% of those over 49 years old. At 12-year estimation, 10.7% of farmers under 39 years old had stopped,
versus 20.5% of those 39–49 years old and 52.2% of those
over 49 years old.
Table II shows the association between baseline factors and early cessation of dairy farming by Cox univariate analysis with delayed entry with age as the time-scale.
Asthma, with a HR of 3.36 (95% CI: 1.50–7.52), was associated with early cessation. Working on a modern or
modernized farm seemed to be a protective factor from
early cessation, but these results did not reach the statistically significant HR level (0.48 [95% CI: 0.22–1.04]). We
found no significant association between sex, smoking
habits, alcohol habits, cardiac diseases, cough, phlegm,
dyspnoea, FEV1/FVC ratio, altitude, and early cessation of
dairy farming. As for FEV1/FVC ratio, 112 (59.0%) farmers had no obstruction, 69 (36.3%) had mild obstruction,
and only 9 (4.7%) had an obstructive syndrome.
In multivariate analysis, no significant interaction was
shown for respiratory function tests. Table III shows the
protective effect of working on a modern or modernized
farm (HR: 0.36, [95% CI: 0.16–0.81]).
Early Cessation and Dairy Farming
TABLE I. Comparison of Baseline Personal and Farms Characteristics
Between Dairy Farmers Analyzed and Dairy Farmers Lost to Follow-Up
Dairy farmers Dairy farmers
analyzed
lost to follow up
(N ¼ 202)
(N ¼ 17)
Age at inclusion,n (%)
39 years
39^49 years
49 years
Sex,n (%)
Male
Female
Smokinghabits,n (%)
Nonsmoker
Smoker
Alcohol habits,n (%)
Nondrinker
Drinker
Cardiac disease,n (%)
No
Yes
Cough,n (%)
No cough
Wintercough less than 3 months
Wintercough more than 3 months
Sputum,n (%)
No phlegm
Winterphlegm less than 3 months
Winterphlegm more than 3 months
Dysnoea,n (%)
No
Yes
Asthma,n (%)
No
Yes
Spirometric dataa
%FEV1 (SD)b
%FVC (SD)b
FEV1/FVC (SD)
%FEF25^75% (SD)b
Numberofcows,n (%)
70
>70
Farm’s size in hectares,n (%)
30
>30
Type of farm,n (%)
Traditional
Modern or modernized
Early quitdairy farming,n (%)
No
Yes
a
TABLE II. Risk of Early Cessation of Dairy Farming According to Baseline
Characteristics in Univariate Analysis
Factors
P
67 (33.2)
67 (33.2)
68 (33.6)
6 (35.3)
4 (23.5)
7 (41.2)
ns
117 (57.9)
85 (42.1)
10 (58.8)
7 (41.2)
ns
148 (73.3)
54 (26.7)
9 (52.9)
8 (47.1)
ns
140 (69.3)
62 (30.7)
13 (76.5)
4 (23.5)
ns
188 (93.5)
13 (6.5)
17 (100.0)
0
ns
178 (88.1)
8 (4.0)
16 (7.9)
15 (88.2)
1 (5.9)
1 (5.9)
ns
175 (86.6)
7 (3.5)
20 (9.9)
16 (94.1)
0
1 (5.9)
ns
163 (82.7)
34 (17.3)
15 (93.7)
1 (6.3)
ns
189 (94.5)
11 (5.5)
16 (94.1)
1 (5.9)
ns
95.7 (11.7)
99.9 (15.0)
80.4 (4.8)
81.1(16.2)
nsc
nsc
nsc
nsc
115 (56.9)
87 (43.1)
9 (52.9)
8 (47.1)
ns
104 (51.5)
98 (48.5)
11 (64.7)
6 (35.3)
ns
19 (9.5)
182 (90.5)
5 (29.4)
12 (70.6)
0.03
99.0 (13.6)
103.1 (13.9)
80.5 (6.2)
85.1 (20.9)
Sex
Male
Female
Smokinghabits
Nonsmoker
Smoker
Alcohol habits
Nondrinker
Drinker
Cardiac disease
No
Yes
Cough
No cough
Wintercough less than 3 months
Wintercough more than 3 months
Sputum
Nophlegm
Winterphlegmless than 3 months
Winterphlegm more than 3 months
Dyspnoea
No
Yes
Asthma
No
Yes
FEV1/FVC (classes)a
FEV1/FVC > 80%
70% FEV1/FVC 80%
FEV1/FVC < 70%
Type of farm
Traditional
Modern or modernized
Altitude
Plain
Mountain
Plateau
HR (95% CIs)b
Pc
1
1.19 (0.67^2.13)
0.54
1
0.85 (0.43^1.68)
0.64
1
0.73 (0.38^1.41)
0.35
1
1.06 (0.37^3.04)
0.90
1
1.58 (0.56^4.46)
1.35 (0.53^3.42)
0.59
1
1.72 (0.53^5.58)
1.23 (0.52^2.91)
0.62
1
1.22 (0.60^2.46)
0.59
1
3.36 (1.50^7.52)
0.003
1
1.71 (0.95^3.06)
0.38 (0.09^1.64)
0.05
1
0.48 (0.22^1.04)
0.06
1
0.60 (0.29^1.25)
0.78 (0.36^1.66)
0.37
a
FEV1/FVC (classes),190 farmers analyzed.
HR (95% CI), hazard ratio with age as time scale and 95% confidence interval.
c
PWald test.
b
152 (75.2)
50 (24.8)
Spirometric data, 206 farmers assessed (190 analyzed and16 lost to follow-up).
Spirometric data were transformed into percentage of ECSC reference values, calculated in relation to sex, age, and height. FEV1, forced expiratory volume in1s; FVC, forced
vital capacity; FEF25^75%, forced mid-expiratory flow.
c
P Student’s test.
b
139
The clinical symptoms and asthma model showed significant interaction between sex and asthma (P ¼ 0.002).
Table IV showed having asthma to be predictive of early
cessation in women (HR: 16.12 [95% CI: 3.28–79.12]):
six women with asthma at baseline all stopped dairy farming. Farm characteristics was a borderline predictive factor
early cessation for men. Among the 108 men dairy farmers with modern or modernized farms, only 20 (18.5%)
140
Mounchetrou et al.
TABLE III. Predictive Factors of Early Cessation of Dairy Farming Using
Cox Multivariate Analysis,190 Dairy Farmers Analyzed
Sex
Men
Women
Smoking habits
Nonsmokers
Smokers
FEV1/FVC
FEV1/FVC > 80%
70% FEV1/FVC 80%
FEV1/FVC < 70%
Type of farm
Traditional
Modern or modernized
HR (95% CIs)a
Pb
1
1.20 (0.61^2.34)
0.59
1
1.09 (0.50^2.38)
0.83
1
2.00 (1.09^3.67)
0.37 (0.09^1.59)
0.03
0.18
1
0.36 (0.16^0.81)
0.01
a
HR (95% CI), hazard ratio with 95% confidence interval.
P Wald test.
b
stopped dairy farming early versus 21 (28%) of the 75
women with modern or modernized farms.
DISCUSSION
The main findings of this study were that (1) working
on a modern or modernized dairy farm seemed to protect
against early cessation, (2) the presence of asthma was a
significant predictor of early cessation, especially in
women.
With adjustment on sex, smoking habits, and FEV1/
FVC classes (Table III), working on a modern or modernized farm was protective against early cessation (HR: 0.36
[95% CI: 0.16–0.81]). With stratification by sex and
TABLE IV. Predictive Factors of Early Cessation of Dairy Farming in Men
and Women Using Cox Multivariate Analysis, 202 Dairy Farmers Analyzed
Men
HR (95% CIs)
Smoking habits
Nonsmokers
Smokers
Asthma
No
Yes
Type of farm
Traditional
Modern or
modernized
a
a
Women
P
b
HR (95% CIs)a
1
0.58 (0.24^1.39)
0.22
1
0.80 (0.12^5.15)
1
1.23 (0.29^5.33)
0.78
1
16.12 (3.28^79.12)
1
0.36 (0.12^1.07)
0.07
1
0.52 (0.17^1.59)
HR (95% CI), hazard ratio with 95% confidence interval.
P Wald test.
b
Pb
0.81
0.0006
0.52
adjustment on asthma and smoking habits (Table IV), we
observed a similar trend in men (HR: 0.36 [95% CI: 0.12–
1.07]) only. The effect of farm modernity on early retirement in men, should be related both to the ventilation/dust
characteristics of modern or modernized farm and/or to
socioeconomic factors. In a previous study of our cohort,
modern farms were also associated with a lower decline in
lung function parameters [Venier et al., 2006]. Similarly,
in a Swedish study following dairy farmers for 14 years
(1988–2002) in southern Sweden, milkers who had
stopped milking during follow-up worked in significantly
older buildings than those who continued to milk [Pinzke,
2003]. In a longitudinal study including 302 swine farmers
at baseline in 1990–1991, only 52 of the 215 farmers followed in 2003–2004, were still working on a swine farm
[Chenard et al., 2007]. This study analyzed factors associated with male swine farmers stopping farming during the
13-year follow-up. In univariate analysis, stopping was associated with a lower percentage of predicted FEV1/FVC
and FEF25–75% and with a small herd size (number of pigs
<400) at baseline. In multivariate analysis, small herd size
at baseline was the only remaining factor influencing cessation during the follow-up.
The Cox univariate analysis showed that asthma was
strongly associated with the early cessation of dairy farming. This ‘‘healthy worker survivor effect’’ due to asthma
has been reported in numerous studies. In a French study,
young military recruits with asthma changed jobs more
frequently than their nonasthmatic counterparts [Le Moual
et al., 2008]; this effect was even greater in those with
moderate as opposed to mild asthma 71% and 52%, respectively. Severity has also been shown to be an important predictor for unemployment, change in jobs, and
disability among individuals with asthma. In the Swedish
study previously mentioned [Pinzke, 2003] about 20% of
dairy farmers stated the reason for stopping milking to be
work-related health problems, including asthma. In another study [Hartman et al., 2003], the slowest recovery from
sick leave was seen in farmers with respiratory diseases
(including asthma) and farmers in the oldest age category.
One cohort study of young adults showed that the rate of
unemployment at the age of 23 years was slightly higher
in subjects reporting current or past asthma, irrespective
of the severity of the asthma [Sibbald et al., 1992]. In a
random sample of 401 adult asthmatics, aged 18–50 years,
seen by pulmonologists and allergy-immunologists in
California, asthma was the reported cause of work cessation in 7% of the subjects and work disability was related
to asthma severity and job conditions [Blanc et al., 1996].
Partial work disability, defined as any change in job duties
or reduction in work hours due to asthma, has been described in 5–20% of adult asthmatics attending specialized
clinics [Blanc et al., 1996; Balder et al., 1998; Mancuso
et al., 2003].
Early Cessation and Dairy Farming
As shown in Table IV predictive factors of early cessation in dairy farming differ between men and women:
asthma was a predictor in women and not in men. Conversely, working on a modern or modernized farm was a
protective factor in men. One reason for the asthma effect
difference observed between men and women could be the
fact that women are more health-conscious. Men are less
likely than women to seek advice and assistance regarding
their health [Woods, 2001]. This has been attributed to
inadequacy in the provision of health services tailored to
the issues and needs of men, and to a prevailing masculine
culture in which men do not place the same priority on
health maintenance and help-seeking as women [Woods,
2001]. Von Bonsdorff et al. found that negative perceptions about work and general life satisfaction were associated with early retirement intentions among women. For
men, good self-rated work ability and perceived good
health were negatively associated with early retirement
intentions [von Bonsdorff et al., 2010].
Although FEV1/FVC below 70% was not a significant
predictor of early cessation of dairy farming (Table III),
FEV1/FVC between 70% and 80% was (HR: 2.00 [95%
CI: 1.09–3.67]). This result may be explained by the low
number of farmers with obstructive syndrome (only
4.7%).
There was no significant smoking effect. This may
reflect the ‘‘healthy smoker effect’’ [Becklake and Lalloo,
1990], that is, the possibility that subjects who start and
who continue to smoke are particularly resistant to the effect of cigarette smoke. Similarly, in 1994 the effect of
smoking on lung function decline disappeared in grain
workers exposed for >20 years [Pahwa et al., 1994].
In our study, the early cessation of dairy farming increased greatly as a function of the farmer’s age at
the baseline. This is important since the agricultural
population in France is ageing. One reason for this increase
may be the duration of exposure, which is correlated with
work-related health problems such as asthma, musculoskeletal disorders, and low respiratory function. Our results
are consistent with the findings reported by Hartman et al.
[2003], that the incidence and the duration of sick leave
increased concomitantly with age. The reason suggested for
this was the increase in the incidence of musculo-skeletal
disorders. de Zwart et al. [1997] also reported that in physically demanding occupations, musculo-skeletal complaints
increase concomitantly with age.
The main limitation of the present study was the incomplete inventory of factors affecting the decision for
early retirement. A systematic review conducted by van
den Berg et al. [2010] on eight longitudinal studies
showed that the important factors for early retirement
were poor health, being single, high physical work
demands, high work pressure, low job satisfaction, and
lack of physical activity in leisure time. Because the
141
cohort we used was not built for this objective, most of
these reasons for stopping work early were not recorded
in the database we used. Moreover, the majority of studies
published on early retirement concern farm workers or salaried workers in others fields; the farmers in our study
were self-employed. Thelin and Hoglund [1994] showed
that farmers changed occupation or retired early less often
than those in other occupations did, whereas more farm
workers changed occupation and retired than did other
workers of the same age.
Because agriculture is one of the most physically demanding and risk-prone professions, poor health, musculoskeletal injuries, and disorders are frequent reasons for
cessation in farming. Hartman et al. [2003] studied selfemployed Dutch farmers and found that musculo-skeletal
injuries and disorders represented 61% of all farmers’
claims for sick leave up to 1 year. These diagnoses
accounted for 58% of the total number of claims for sick
leave longer than 1 year.
CONCLUSIONS
We observed that working on traditional farms and
having asthma were predictive factors for early cessation
of dairy farming. However, there was no effect of other
respiratory symptoms or obstructive syndrome. Most studies on the early cessation of work have been related to
only one gender or to salary scale. This is the first study
to examine predictive factors of early cessation of dairy
farming in self-employed men and women with a 12-year
follow-up.
ACKNOWLEDGMENTS
We wish to thank the members of the medical unit of
the MSA in the Doubs who helped us to organize the data
collection and Nancy Richardson-Peuteuil for her editorial
assistance. The baseline data collection has been supported by grants from the Réseau National de Santé Publique (FIS) and INSERM (CNEP 93 CN 20). The 1999
follow up has been supported by grants from the SERF
Group (EA 2276), French Ministry of National Education,
Research and Technology, and by the CNMRT (Comité
National de lutte contre les Maladies Respiratoires et la
Tuberculose ¼ National Committee against Respiratory
Diseases and Tuberculosis). The 2006 follow up has been
supported bu grants from the the SERF Group (EA 2276),
French Ministry of National Education, Research and
Technology.
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