Predictors of early cessation of dairy farming in the French Doubs province 12-year follow-up.код для вставкиСкачать
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: firstname.lastname@example.org 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. , 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.  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.  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  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.  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. 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