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The dangers of dairy farming The injury experience of 600 workers followed for two years.

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American Journal of Industrial Medicine 21:637450 (1992)
The Dangers of Dairy Farming: The Injury Experience
of 600 Workers Followed for Two Years
David S. Pratt, MD, Laura H. Marvel, BSN, Diane Darrow, BS,
Lorann Stallones, PhD, John J. May, MD, and Paul Jenkins, MS
In order to better understand the work-related injuries sustained on central New York
dairy farms, we undertook a two-year population-based study of 600 farmers and farm
workers on 201 dairy farms. During the observation period, 1984-1986, 151 persons
had 200 injuries, giving an injury rate of 16.6%/year (166 injuries/1,000 workers/year).
Men were injured more often than women (p 5 0.01). Injured workers were older (p
5 0.01), worked more hours (p 5 0.001), and had heavier workloads than noninjured
workers (p 5 0.001). The growing and harvest seasons had the most injuries; winter the
fewest. More than 2/3 of the injuries occurred in the afternoon. Owner/operators, often
the most experienced, knowledgeable people on the farms, were most often hurt. Those
working more than 60 hours/week, with greater than 30 acres under tillage/worker, had
a relative risk of 2.76 compared with all other workers. The attributable risk for this
group was 51%. There were two fatalities, both involved owner/operators. Our findings
suggest that previous studies may have underestimated the risks faced by farmers. Dairy
farming in central New York is very dangerous work. Those who own and operate these
dairy farms are most often hurt and killed. Analysis of events on individual farms will
be reported separately. 0 1992 Wiley-Liss, Inc.
Key words: farm injuries, occupational injuries, agricultural exposure, dairy farming, injury epidemiology
INTRODUCTION
Rural America’s landscape is dotted with the familiar silhouette of family
farms. Over the past three decades, economic changes and improved agricultural
practices have resulted in a decreasing number of farms producing more goods and
services [Census of Agriculture, 19871.
Because agriculture is often associated with fresh air, safe, hard work, and
robust good health, reports to the contrary are often surprising to those not familiar
with the farm as a work place. Beginning in the 1950s, agricultural engineers and
safety specialists reported information that began to paint a disturbing picture of real
The New York Center for Agricultural Medicine and Health, The Mary Imogene Bassett Hospital,
Cooperstown, NY.
Lorann Stallones’ current address is the Department of Environmental Health, Colorado State University,
Fort Collins, CO .
Address reprint requests to David S. Pratt, M.D., Director, New York Center for Agricultural Medicine
and Health, One Atwell Road, Cooperstown, NY 13326.
Accepted for publication September 24, 1991.
0 1992 Wiley-Liss, Inc.
638
Pratt et al.
danger on American farms. [Hoff, 1969; Jensen, 1980; Knapp and Piercy, 1966;
Schnieder, 19801. These reports had some methodological limitations, but drew
attention to potentially serious hazards for farmers.
Numerous clinical reports from emergency rooms and other sources described
farm injuries and their severity. [Cogbill and Busch, 1985; Doyle, 1984; Maxim et
al., 1954; McKinnon et al., 1967; Powers, 19501. These reports served to support the
agricultural engineers in their concerns.
Well-designed surveillance of agricultural injuries is scant. Both the National
Safety Council and the U.S. Labor Department’s Bureau of Labor Statistics report
work-related agricultural injury rates. Each has limitations that are substantial. The
Bureau of Labor Statistics samples farms with 11 or more employees (about 5 % of all
U.S. farms) and reviews only the injuries that regulations require be kept on file
(OSHA Form 200). The National Safety Council uses volunteers to report on a
sample selected by a cooperating group or agency in each of 30 states. Recent
criticism and recommendations from the National Research Council should help
improve the data collection problems. [National Research Council, 19871.
We were concerned that clinical reports and emergency room reviews omitted
less serious, but important work-related illnesses, while the above noted surveys
might not sample or collect data in a representative fashion. In order to deal with these
apparent problems, we chose to study in detail the work experience on nearby dairy
farms in Otsego County, New York. Our hope was to be able to accurately report the
injury experience of a defined population of dairy workers, followed for two years.
METHODS
The Study Group
The farms in the study were selected from the U.S. Department of Agriculture’s
(USDA) list of all farms in Otsego County, New York. This list is based on the
Agricultural Census done by the United States Department of Agriculture, and its
annual subsample update. At the time of the enumeration in 1984, there were 540
farms with annual gross receipts of at least $10,000 operating in the county. More
than 95% of these were dairy farms. All farms in the final study group were dairy
operations.
Every farm operator was contacted by mail and asked to participate in a twoyear study of agricultural injuries. We received agreements (verbal and written) from
those responsible for 220 farms. We tested our sample of farms for selection bias by
comparing their herd size with the herd size for all farms in the county. No difference
was noted. Zip codes of participating farms were also plotted to evaluate geographic
distribution. Study farms were distributed in each township of the county.
Over a two-year observation period, 19 farms left the study. Eighteen farms left
either because of financial hardship or government buyout programs. One farm no
longer wanted to participate. We analyzed the size and worker characteristics of the
farms that stopped providing information and found no bias introduced.
At the completion of the study in 1986, information was available on 600
workers from 201 farms. A worker was defined as a person who worked at least 10
hours/week on the farm in any capacity and was older than 10 years of age. We used
10 years of age as a cut-off for farmers since no one under 10 years worked more than
one hour per day and children under 10 years were not felt to fairly represent the
Dangers of Dairying
639
worker pool. We used 10 hours per week as the lower limit of “workers” since this
would only amount to about one average farmer’s day. Those working less than 10
hours a week could not be thought of as farmers.
Data Collection
Study farms were observed for 24 months between 1984 and 1986. Initial
demographic information was obtained by mail questionnaire. The same information
was reconfirmed during the second year by telephone. All workers on the farms were
enumerated, as were their work hours. The characteristics of each farm were recorded, including size (in terms of animals and acres), line of business, receipts, and
equipment in use.
After the enrollment questionnaire, each farm was called every other month for
two years. Two phone interviewers made all the calls. Calls were structured using a
written statement. Phone respondents (usually the farm wife) defined all injuries on
their own farms. No attempt was made, beyond the written statement, to prompt or
discourage reporting of any job-related injury. No reports were excluded, except, for
the purposes of this study, injuries in those who did not meet our definition of a
worker. All work-related incidents were recorded. Injuries were often written on the
family calendar, and farms were anticipating our calls. Information collected on each
injury included person injured, age, sex, time, place, extent of injury, and consequences in terms of medical care and time off work.
During the study period, over 3,200 phone calls were made. Information was
entered into a data base on an IBM-XT PC. All data were edited after entry and
checked for accuracy. Analysis was done using SAS software on a Digital Equipment
Corporation Microvax machine.
For categorical variables, all comparisons reported were made using chi-square.
Analysis of continuous dependent variables, such as injury rates, acres under tillage,
and number of co-workers, was performed using t-tests for dichotomous independent
variables and analysis of variance for independent variables with more than two
levels. A p value of less than or equal to 0.05 was taken as significant.
Those variables found to be significant at the univariate level were entered into
a multiple logistic regression equation with the absence or presence of an injury as the
outcome. Stepwise procedures were then employed to obtain a reduced model containing only independent predictors of an injury.
As a check on the accuracy of the reporting from the study farms, we reviewed
the emergency room records of 70 injuries reported to have been seen at a local
emergency room. We uncovered one additional injury in this way. In no instances
were cases missing from the emergency room records if they reported having received
care there.
Injuries were scored for severity from one to four. Simple injuries not requiring
medical attention or lost time from work were given a score of one, more serious
injuries requiring medical attention and/or time off work were given higher scores, as
explained in detail below.
RESULTS
Crude Injury Rates
Two hundred injuries occurred among the 600 workers on 201 farms during the
1984-1986 observation period. The crude rate of injury was 166 injuries/l,000
640
F’ratt et al.
6
0.4
6
0.3
4
3 Injuries
per
2 1,m
hours
1 worked
Injurles
per
loo
workers 0.1
0
0
11-20
21-30
31-40
41-50
51-60
61-70
71,
Age
Inlury Rate
RaW1000 hrs. worked
Fig. 1. Injury rates adjusted for farmers’ age and mean hours worked.
workerdyear, or 16.6%. Men had an overall injury rate nearly three times higher than
women.
Persons
There were 151 individuals injured during the study. The majority of workers
(79%) were injured once; twenty-one workers (14%) were injured twice. Ten additional workers had three or more injuries, including one man with six events.
Women workers numbered 137; they sustained 19 injuries for an annual rate of
69/1,000 or 6.9%. The 463 men in the study had 181 injuries for an annual rate of
195/1,000 of 19.5%. The women were injured at a rate about one-third that of men
(rate ratio of 1:2.8) when workers at risk was used as the denominator. This difference was highly significant (p 5 0.001).
In order to explore the male/female disparity further, we calculated injury rates
by mean numbers of hours worked. Women had 1.59 injuries/l ,OOO workerdhour and
men 2.98 injuries/l ,OOO workerdhour. This difference is significant (p 5 0.05) and
confirms the unadjusted trends.
Age-specific injury rates were examined to look for special risk groups. Figure
1 shows that injuries are highest in the 31-40 and 51-60 age groups. Age-specific
rates, though helpful, need further correction for exposure to give a full picture.
Figure 1 also shows injury rates for worker groups corrected for reported hours of
exposure. This figure demonstrates the persistence of peaks in 31-40 and 51-60
age-groups. The pattern of injury by decade remains similar after the adjustment for
hours of exposure.
In all but five injuries, we were able to identify the type of worker involved.
Examination of the injury pattern in each worker group produced some striking
results. The owner/operators made up about one-third of all workers, yet had 62% of
the injuries followed by relatives (24%) and hired men (14%). As shown in Table I,
the increased number of injuries is explained in part by the size of this group and its
Dangers of Dairying
641
TABLE I. Injuries by Worker, Rate on the Farm, and Population at Risk (Otsego County, NY)
Owners
Relatives
Hired men
Injuries"
Population
at riska
Mean weekly
hours at risk
Injury rate/
population
Injury/hours
122
46
27
203
292
100
79.0
51.7
53.7
0.60
0.16
0.27
1.54
0.89
0.50
"Five of the 200 injuries were incurred by people in which the type of worker was unknown. We were
unable to contact these farms for verification of worker type.
high number of hours on the job. When we corrected for these factors, we still found
that owner/operators had the highest injury rate (p I0.05).
The gender, worker type, and age variables were highly related, in that 99% of
the ownedoperators were men and 73% of these were in the fourth, fifth, and sixth
decades of life. Multiple logistic regression procedures revealed that sex and age do
not contribute significantly to the probability of an injury in an equation which
contained the type of worker. Thus, the relationship between age, gender, and injury
rates may be affected by the preponderance of injuries among the owner/operators.
Place
The dairy farm consists of a wide variety of work environments. In order to
explore the dangers of these different locales, we examined injuries by their place of
occurrence. Figure 2 shows the location of the worker when the injury occurred. The
barn was obviously the most common location for injuries (p 5 0.002). This frequency of barn injuries is not surprising, given the nature of dairy farming and the
limited field work that goes on during the five winter months (November through
March). Another factor in the high number of barn injuries is the type of work done
in this environment. It is in the barn where the dairy worker interacts with both
machinery and animals-an average of 50 milking cows twice daily, 365 days per
year. As shown in Table 11, it was the interactions with machinery, followed by those
with animals, which most commonly caused injury.
Time
Although very few farms reported the exact hour of an injury, 93% were able
to report that an injury occurred in the morning or afternoon. Two-thirds of the
injuries took place in the afternoon.
Injuries occurred every day of the week. No day had a significantly increased
number when compared with other days of the week. Only 60% of respondents could
recall the day of the reported injury.
Injuries were much more common during the growing seasons. This difference
was significant (p 50.01) (Figure 3).
Injury Detail
Body part injured is shown in the human form diagram (Figure 4). It can be
readily seen that the extremities were the most frequently injured parts of the body.
In general, illnesses like colds and urinary tract infections were not reported as
work-related and hence do not appear in the data base. In our chest/lung category
(13% of all injuries), 52% were trauma related (rib fractures, usually), while 48%
642
Pratt et al.
60%
SOX
40%
30%
20%
10%
0%
Barn
Field
Sllo
Barnyard
Other
Shop
Location
Fig. 2. Percentage of injuries by location on the farm.
TABLE 11. Farm Injuries
by Causative Factor
(Otsego County, NY Dairy
Farms, 1984-1986)
Machinery
Animals
Other
Falls
Respiratory
Chemical
35%
32%
16%
8%
7%
2%
were ailments like silo filler’s disease and organic dust toxic syndrome (0DTS)both of which could be considered work-related injuries.
Table I11 outlines the severity of the self-reported injuries based on medical
visits and lost time from work. Seventy percent sought medical care, demonstrating
that few trivial injuries were reported. The injuries sustained were often disabling;
31% of those injured lost time from work. Eighteen percent were serious enough to
put people off work for four or more days. The average lost time was 10.7 days; the
median was eight days.
Having seen the high rate of injuries for those in the 3 1-40 age-group, we were
interested to see if they had more severe injuries. No greater severity in this age-group
was found. Likewise, we noted no increase in disability or severity analyzed by age
or sex.
Farm Characteristics Associated With Injuries
Injured persons tended to work on larger farms with more acres under tillage (p
0.001), but with fewer co-workers (p 5 0.001). They also worked more hours than
non-injured persons (p 5 0.0001). The long hours and smaller crews suggested that
5
Dangers of Dairying
643
20%
15%
10%
5%
0%
Wlnter
- (DJF)
Month
Sprlng
(MAMI
Summer'
(JJA)
Season
(p<O.Ol)
Fig. 3. Percentage of farm injuries by season.
individual workloads were important. Two ratios were set up to examine this workload hypothesis. These ratios were: workers to milking cows, and workers to acres
under tillage. On most dairy farms that grow their own forage, these ratios are, by
necessity, proxies for one another. Both ratios were highly and directly associated
with injuries (p 5 0.0001).
Owner/Operators
After age and exposure adjustments, owner/operators emerge from our data as
being at particular risk for injury. These men and women worked longer hours, were
older, and, even when injured, seldom missed days of work. Only 27% of injured
owners took a day off, whereas 52% of hired help took days off with injuries.
Detailed analysis showed that owners working more than 60 hours per week, and with
farm workloads greater than 30 acres per worker, had a relative risk of 2.78 compared
with all other workers. They had an attributable risk of 51%, based on the above
characteristics.
Seasonal Patterns
Earlier in the Results section, we described the injuries by location on the farm.
Figure 5 shows the increase in field injuries as the work becomes more intense in the
spring and early summer. The field injuries rise again (apparently) with haying and
the taking in of corn in the fall. Barn injuries, by contrast, appear more evenly
distributed throughout the year.
Another aspect of the patterns illustrated in Figure 5 confirms our clinical
experience. Here we can see a gradual increase in silo injuries as the year draws closer
to the corn harvest. In November, a full 25% of all silo-related injuries occur.
644
Pratt et al.
Fig. 4. Body location of farm injuries.
Deaths
During the two years’ study, two men lost their lives. The first man, age 39,
died when a tractor, with a front end loading device, turned over and crushed him.
His tractor was not equipped with a rollover protective structure. He was found
several hours after the incident and pronounced dead at the scene. The second death
occurred when a 52-year-old farmer suffered a fatal heart attack while hammering on
a corn picker in his barnyard. He had had a prior history of coronary artery disease.
He died at a local hospital within hours of his infarction.
These two events are described, but not further analyzed. Two events do not
allow fair estimates of fatality rates on our farms.
Dangers of Dairying
645
TABLE 111. Injuries by Severity Score for 1984-1986 Observation
(Otsego County, NY)
Score
number
Number of
iniuries
Definition
59
No medical care, no lost time
Sought medical care, no lost time
Sought medical care, 5 3 days lost
Sought medical care, 2 4 days lost
1
2
3
4
%
30
39
13
I1
21
31
18
30%
i..
...
*
...
... ......
.... .,.(.. ..... .._..
.. ..
, .
. ..
... ...
. .
; j. ’ . . .
20%
..
16%
10%
i
6%
0%
J
F
M
A
M
J
J
A
S
O
N
D
Month
+Barn
*Fleld
..*,.
Silo
Fig. 5 . Percentage of injuries by farm location and month.
DISCUSSION
Our results show that a surprisingly high rate of 166 injuries per 1,000 workers
occurred each year (16.6%). Since some workers sustained more than one injury, the
rate for individual workers injured is somewhat lower, but still quite high at 12.5%
of all workers injured per year. Thus a worker has a 1 in 8 chance of being injured
each year on the job.
Occupational injuries are reported differently by various sources as shown in
Table IV [Jansson, 1987; Michigan Department of Public Health, 1989; National
Safety Council, 1989; U.S. Department of Labor Bureau of Labor Statistics, 19831.
The National Safety Council’s 1989 Accident Facts reported the rate of injuries on
dairy farms in 35 states based on voluntary study data. They estimate a rate of 22.3
farm work injuries per 1,000,000 hours on the job. After correcting our rate to meet
the NSC definition of an injury: “. . . an injury . . . requiring professional care or
causing one half day’s lost work . . . ,” we had 42.7 injuries/l,000,000 hours
worked, or about 2.0 times their estimate. This difference may be the result of the
method of active surveillance we used and a maximum 60-day recall, as opposed to
their 90-day recall and volunteer surveyors providing reports.
We chose a more liberal definition of an injury based on our clinical experience
of farmer stoicism and doctor-avoidance. Had we used the National Safety Council’s
646
Pratt et al.
TABLE IV. Comparison of Other Data Sources With Otsego County Dairy Farms
Injuries/] O6 hours workedlyear
Sweden
1983
Michigan
1987
National Safety
Council 1988
(Dairv)
Otsego County,
New York
1984-1986
24.6
28.5
22.3
42.7
TABLE V. Variations in Iniurv Definitions
Pratt et al.
Injury
definition
Any selfdefined acute
illness episode
National
Safety Council
Michigan
Jansson
BLS
Episode requiring
professional care
or causing f i day’s
lost work
Same as
National
Safety
Council
Episodes
requiring
care in
hospitals or
emergency
rooms
Self-defined
reported
according to
OSHA standards
definition, many important injuries would have been omitted. A good example is a
farmer who was sprayed with caustic hay preservative, burning both his hands and
face. He neither sought care nor lost time from work. In other settings he might well
have done both. We feel his was an important injury to report.
A recent comprehensive one-year study from Sweden reported an injury rate of
24.6 injuries/1,000,000 hours worked [Jansson, 19871. This figure is very close to the
NSC estimate, but well below the rate we report. The Swedish estimate is based on
injuries requiring medical care-which is available at no charge to injured workers.
Their reporting relied generally on emergency room records. The Swedish farms
involved included diverse agricultural activities, including dairying, beef production,
pork, and feed grains. This diversity may help explain the lower rate.
The U. S. Department of Labor reports injuries in American business as well. In
the last published Bulletin, they reported injuries in all productive agriculture (SIC
codes 01-02) for 1981 to be 12.8 injuries per 100 full-time workers [U.S. Department
of Labor Bureau of Labor Statistics, 19831. This rate is calculated on the basis of a
40-hour week.
The injury case definition used by the Bureau of Labor Statistics (BLS) is
similar to ours. When we adjust our data for full-time workers (77% of the work
force), we find a rate of 8.24 injuries/lOO workerdyear. This rate is smaller than the
BLS all farm estimate. The small farm (1 1-19 workers) BLS figure, however, is quite
a bit lower at 6.3 injuries/lOO workerdyear. Unfortunately, the BLS does not collect
any information on farms smaller than 11 workers (roughly 95% of all American
farms).
Recently, the Michigan Department of Public Health published a one-year study
of injuries in two counties [Michigan Department of Public Health, 19891. They used
written questionnaires and required farms to report injuries that met the NSC definition. This survey covered over 2,000 workers on 785 farms. The estimated rate of
injuries for this farm group was 50/1,000 workerdyear.
Information was obtained on only two injuries on any given farm during the
study period. Adjusting our rate to their methods, we find 108 injuries/l ,000 workers/
year. This is nearly twice Michigan’s and may be affected by the fact they used a
Dangers of Dairying
647
one-year recall period, limited case reporting, and surveyed several kinds of agriculture, including grains, dairy, and others. The Michigan group also reported their
incidence in the injuries/l ,000,000 format. This is shown in Table V along with other
estimates cited. These varied methods of data collection, injury definition, recall
period, and rate reporting argue strongly for a unified system of defining and following agricultural injuries. Improving the quantity and the quality of farming injury
data would help considerably in planning intervention strategies and evaluating them.
We were surprised to see the marked difference in injuries to men compared
with women (2.8:l). While, in general, women are less often injured than men, we
did not anticipate the high ratio of men to women. In data presented by the National
Health Interview Survey (NHIS), they found injury rates for white women to be
comparable to white men in agriculture. Black women, however, had an injury
experience similar to that seen in our figures. The NHIS black men to women ratio
was 3.9:l [Kaminski and Spirtas, 19801. Injuries seen in emergency rooms in Sweden, reported by Jansson, showed a sex ratio of 6.76:l male to female. [Jansson,
19871. One possibility is that women do fewer risky tasks on the farm. We did not
find that women differed appreciably from men when we examined the type of
injuries they sustained, where they were injured, or the severity of their injuries.
Another, more interesting possibility, is that women are safer workers. Injury rates on
the job by sex are very hard to locate beyond the NHIS figures described above.
One of the most interesting published studies on causative or explanatory factors
in work place injury came from Kriebel [ 19821. He identified a number of factors
which helped explain differences in injuries among various kinds of work. One of his
postulates is that injury frequency is explained in part by rate of new hires. This factor
would reflect the relative number of inexperienced workers on the job at any one
time. To test this hypothesis in the study group, injury rates were examined by age
decile. In contrast to Kriebel’s hypothesis, we found that injury rates were highest in
the 3rd and 5th decile. These findings are similar to Jansson’s experience in Sweden
[Jansson, 19871.
Another factor of importance in Kriebel’s work is the correlation of energy
consumed per worker with injury severity. We found that injuries associated with
machinery were more severe. While only 50% of animal injuries required a visit to
a health provider, 80% of those associated with machinery necessitated medical
attention. Thus, in this instance, we have evidence to support Kriebel’s observation.
We were very interested to note that the people who own and operate the farms
are most often hurt. This certainly has potential economic significance. Our observation was shared by Sell and others in a description of power-take-off (PTO) injuries. [Sell et al., 19851. The relative risk of hard-working owner/operators was 2.76.
Owners with high-risk characteristics had nearly three times the likelihood of injury
compared with other workers. This finding has important implications. The owner/
operators are the most experienced individuals in farming today. Their risk suggests
that the best of the work force are at the highest risk-a very serious situation. An
even greater concern arises from the recent trend in American farming toward larger
farms, more cows, more mechanization, and fewer workers. These trends for the
Northeast are shown in Figure 6. The economic trends are moving dairy farming in
New York toward increasing risk for workers [New York Department of Agriculture
and Markets, 19901.
The occurrence of disabling injuries on small farms is a serious problem. Given
648
Pratt et al.
INCREASE IN LARGE HERDS ON DAIRY FARMS
IN NEW YORK
1984
- 1988
0.370
0.350
0.330
0.310
0.290
0.270
0.250
4
I
1984
1985
1986
1987
1988
Years
CHANGE IN NUMBERS OF ALL NORTHEAST
AGRICULTURAL WORKERS
1984
170r
160.-
0
\
' 0
150-140130
- 1988
\
--
120 -1104
i
1984
1985
1986
1987
1988
Years
Fig. 6. Increase in large herds on New York dairy farms contrasted with the decrease in numbers of all
Northeast agricultural workers.
the fact that owner/operators were most often hurt and that 20% of all injuries entailed
four or more days of disability, it seems that the injuries we reviewed were likely to
have serious economic consequences. Just over 30% of the injuries had attendant lost
time. This is considerably smaller than the Swedish experience, where they had 46%.
This may be explicable, in part, based upon the insurance scheme used by the Swedes
to compensate injured farm workers [Jansson, 19871.
The finding that most of our injuries occurred in the afternoon is consistent with
many other reports of both fatal and non-fatal farm injuries [Hoff, 1969; Jansson,
Dangers of Dairying
649
1987; Pugh et al., 1974; Field and Toemehlen, 1982; Goodman et al., 19851. Most
authors have postulated fatigue as explanatory of afternoon injury rates.
CONCLUSIONS
Our investigation strongly supports other information suggesting that agricultural work injuries are frequent, severe, and often disabling. It does appear that
women in our dairy group have fewer injuries than men. This experience has been
reported for much of injury research [Baker et al., 19841. New injuries on our farms
follow several trends and tend to occur more frequently when the workloads are
greatest. Other studies support this finding [Michigan Department of Public Health,
19891.
The serious plight of the owner/operator deserves special mention. Our information suggests that these men and women work almost 80 hours per week and have
the highest risk on the farm. Both of our deaths were owner/operators. The owner/
operator is the linchpin of America’s family farm. Richard Rhodes’ recent fictionalized account of a year on a Missouri family farm repeatedly shows the skill, knowledge, and dedication of these people [Rhodes, 19891. It seems to us that the social
situation described in our study deserves public review. A recent study done by
economists at Cornell reported that returns to labor and management were negative on
31 % of New York dairy farms. The mean income per operator was $1 1,042 per year
[Smith et al., 19871. If this were representative of our owner/operator’s return, they
would be earning $2.70 per hour.
One could conclude that the dairy farmers are keeping the price of food low by
keeping labor costs down (his or her time). Our data suggest that these long hours
result in injuries and illness. Are family farmers providing a de facto subsidy of our
food prices at a personal cost in injuries, illnesses, and deaths? Clearly, further study
is needed, but a dark picture of family farming is emerging, which should cause all
of us to pause and reflect on the “inputs” of our food system and what their value
represents.
The analysis of the experiences of individual farms will be reported in a separate
manuscript. We have purposely avoided addressing farms as a unit of analysis for this
paper to the extent possible.
ACKNOWLEDGMENTS
This work was supported, in part, by funds from the Stephen C. Clark Foundation and by the people of New York State.
REFERENCES
Baker SP, O’Neill B, Karpf R (1984): “The Injury Fact Book.” Lexington, Massachusetts, Lexington
Books, p 313.
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