WP3 Food quality and safety
T1 On farm risk analysis
WP3T1L1EE Dairy Farm Risk Analysis 1
[E-A 1]
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The goal of contemporary keeping systems is to create to the farm animals the
environment, which favourably influence to their health, welfare and production ability
(Bickert and Radostits, 2001). Appearance of diseases among the farm animals is often
caused by mistakes made by man or deficiency of knowledge. In modern animal
husbandry the most frequent diseases are related with keeping conditions (keeping
technology, microclimate, organisation of labour) (Ekesbo, 1988). It means that the
vulnerability of animals depends on keeping conditions. (The vulnerable animal
...,1996).
The changes in farm animals keeping conditions influenced also to the veterinary
practice: to the treatment of the individual sick animals focused veterinary practice
changed step by step to a more herd-oriented preventive veterinary practice. For this
reason different herd health monitoring programs have been created and put into practice
(Diesch, 1988; Ekesbo jt, 1994; Saloniemi, 1991; Bartlett jt, 2001; Sviland and Vaage,
2002).
Key elements in such a programme include:
a strengths–weaknesses assessment and priority settings at the start,
clinical animal inspection,
farm inspection,
data monitoring,
herd problem analysis,
the interpretation of collected information including putative risk factors for disease
occurrence,
the development and application of preventive procedures and the critical monitoring of
their implementation (Noordhuizen and Collins, 2002).
Health monitoring
The dairy herd health monitoring systems have been created in the most European
countries: in Sweden (Ekesbo, 1988, Ekesbo et al., 1994), in Finland (Saloniemi, 1991),
in Denmark (Bartlett et al., 2001), in Norway ((Sviland and Vaage, 2002) etc.
Monitoring is the making of routine observations on health, productivity and
environmental factors and the recording and transmission of these observations
(Thrusfield, 2001). The health monitoring makes possible to determine the risk factors
(Frei et al., 1997).
The risk factors of diseases [E-A 2]
Risk factor is a factor which characterizes an animal or environment and which existence
increases the probability of appearance of diseases in the herd (Waldner, 2001). The risk
factors are divided usually into two groups:
a) risk factors of a herd (external or environmental risk factor). These factors such as
physical, chemical and biological impacts, keeping technology, organising of work,
dealing with animals etc. originate from environment and influence all animals in the
herd (Ekesbo et al., 1994).
b) risk factor of single animal (individual or internal risk factors) like age, breed,
reproduction cycle, productivity, genetical predisposition etc. (Ekesbo and Oltenacu,
1994).
For the evaluation of the effect of these risk factors different descriptive and theoretical
methods of epidemiology are used. Usually the next parameters are used for the
characterization of health state and risk factors in the herd: disease prevalence rate,
disease incidence, incidence rate, cumulative incidence rate, confounding factor, relative
risk, adjusted relative risk (Noordhuizen et al., 2001; Thrusfield, 2001).
Quite often in the case of disease the next causal chain exists: environmental factor
change of behaviour disease Adisease B (Ekesbo, 1991; Hartung, 1994). In
connection with diseases the farmers sustain great economical losses. For example the
economical losses caused by diseases of dairy cows are 182-227 EUR per cow in the
Netherland (Dijkihuizen and al., 1997). The expenses caused by most often diseases of
the herds for 100 cows (mastitis, metritis, ovulatory dysfunction, retained placenta,
dystocia etc.) are between 1200 – 13600 (average 6300) £ per year in UK (Kossaibati and
Esslemont, 1997). For the prevention of multifactorial diseases is very important to
ascertain the existence of causal chain and to determine their hierarchy of harmfulness of
each risk factor in the process of disease. It helps to work out an effective program for the
prevention of diseases in concrete herds and to organise effective prophylaxis (Osteras
and Leslie, 1997, Gröhn and Rajala-Schultz,2000).
The risk factors of dairy cows’ diseases
Udder diseases
[E-A 3]
Multifactorial are also the most prominent group of diseases of dairy cows – udder
diseases. Among them the most frequently is diagnosed mastitis, which causes the
greatest economical losses for farmers in dairy cattle farming (Natzke et al., 1972; Dohoo
et al., 1984; Jones et al., 1984; Fetrow and Mann, 1991; DeGraves and Fetrow, 1993;
Deluyker et al., 1993; Swedish Dairy Association, 2001). By Saloniemi et al. (1986) more
than 40% of mastitis cases in high producing herds are induced by environmental risk
factors.
The next factors are found to be risk factors of udder diseases:
1. Environmental risk factors
-microclimate
-type of house, constructions, stalls, mangers
-type and amount of bedding
-manure removal
-milking (aggregates, technique, hygiene)
-nutrition
-working personnel
(Ekesbo, 1966; Saloniemi, 1980; Saloniemi and Näsi, 1981; Koskiniemi, 1982; Oltenacu
et al., 1990; Schuccen et al., 1991; Matzke et al., 1992; Saloniemi, 1996; Faye et al.,
1997; Østerås and Leslie, 1997; Eikman, 1998; Elbers et al., 1998; Barkema et al., 1999;
Whitakier et al., 2000; Peeler et al., 2000; Menzies and Mackie, 2001)
-size of herd
(Saloniemi and Roine, 1981; Willesmith et al., 1986; Sviland and Waage, 2002)
-keeping technology
(Ekesbo, 1966; Bendixen et al., 1988b; Matzke et al., 1992; Østerås, 1994; Valde et al.,
1997; Faye et al., 1997; Whitaker et al., 2000; Hultgren, 2002)
- season
(Saloniemi and Roine, 1981; Bendixen et al., 1988a; Morse et al., 1988)
2. Individual risk factors
-breed
(Ekesbo, 1966; Bendixen et ali., 1988a)
-age (number of lactations)
(Morse et al., 1987; Bendixen et al., 1988b)
-production
(Faye et al., 1997)
Uterine infection
[E-A 4]
1. Environmental risk factors
-keeping technology
-season
-size of herd
(Kaneene and Miller, 1994; Bruun et al., 2002)
2. Individual risk factors
-breed
-age (number of lactations)
-previous diseases (dystocia, retained placenta etc.)
(Kaneene and Miller, 1994; Bruun et al., 2002)
Metabolic diseases [E-A 5]
1. Environmental risk factors
-season
-keeping technology
-herd size
-nutrition
-keeping conditions
(Ekesbo, 1966; Saloniemi and Roine, 1981; Bendixen et al., 1987b; Gustafsson et al.,
1995; Waage, 1994; Valde et al., 1997; Houe et al., 2001)
2. Individual risk factors
-breed
-age (number of lactations)
-production
(Ekesbo, 1966; Bendixen et al., 1987b; Waage, 1994; Houe et al., 2001)
Retained placenta [E-A 6]
1. Environmental factors
-season
-keeping technology
(Ekesbo, 1966; Bendixen et al., 1987)
2. Individual factors
-breed
-age (number of lactations)
-previous diseases (dystocia, parturient paresis etc.)
(Ekesbo, 1966; Bendixen et al., 1987)
Foot diseases [E-A 7]
1. Environmental factors
-keeping technology
-floor
-keeping conditions
-type of house, stalls, mangers
-manure removing system
-bedding
-nutrition
(Ekesbo, 1966; Näsi and Saloniemi, 1981; Rowlands et al., 1983; Thysen, 1987; Faye and
Lescourret, 1989; Philipot et al., 1994; Bergsten, 1994; Bergsten, 1995; Bergsten and
Herlin, 1996; Bergsten and Frank, 1996; Østerås and Leslie, 1997; Busato et al., 1999;
Weary and Taszkun, 2000; Whitaker, et al., 2000; Bergsten, 2001; Hultgren, 2002;
Vermunt, 2004; Guard, 2004; Scaife et al., 2004)
2. Individual factors
-breed
(Bergsten, 1994)
Diseases of digestive system [E-A 8]
1. Environmental factors
-nutrition
-keeping conditions (building, constructions)
-labour organisation
-microbes
-working personnel
-season
(Vannier et al., 1983; Rohrbach et al., 1999)
2. Individual factors
-resistance of organism
-productivity
-previous diseases (metritis, ketosis, mastitis etc.)
(Vannier et al., 1983; Grohn and Bruss, 1990;
Ovulatory dysfunction
[E-A 9]
1. Environmental risk factors
- herd size
- keeping technology
(Laben et al., 1982; Zörlag, 1983; Taylor et al., 1985; Rautala (1991; Østerås and Leslie,
1997; Valde et al., 1997)
2. Individual risk factors
- breed
- productivity
- previous diseases (retained placenta, dystocia, mastitis etc.)
(Emanuelson and Bendixen, 1991; Kristula and Bartholomew, 1998)
Dystocia
[E-A 10]
1. Environmental risk factors
- season
(Bendixen et al., 1986)
2. Individual risk factors
- number of calving
- age
- breed
- sex of calf
- twins
- previous dystocia
(Ekesbo, 1966; Bendixen et al., 1986)
Literature
[E-A 11]
Barkema, H. W., Schukken, Y. H., Lam, T. J. G. M., Beiboer, M. L., Benedictus, G.,
Brand, A. Management practices associated with the incidence rate of clinical mastitis.
Journal of Dairy Science, 82; 1999; 1634–1654.
Bartlett, P. C., Agger, J. F., Houe, H. Willeberg, P., Lawson, L. G. Incidence of
clinical mastitis in Danish dairy cattle and screening for non-reporting in a passively collected
national surveillance system. Preventive Veterinary Medicine, 48; 2001; 73–83.
Bendixen, P. H., Vilson, B., Ekesbo, I., Åstrand, D. B. Disease frequencies in dairy
cows in Sweden. II. Retained Placenta. Preventive Veterinary Medicine, 4; 1987a; 377–387.
Bendixen, P. H., Vilson, B., Ekesbo, I., Åstrand, D. B. Disease frequencies in dairy
cows in Sweden. V. Mastitis. Preventive Veterinary Medicine, 5; 1988a; 263–274.
Bendixen, P. H., Vilson, B., Ekesbo, I., Åstrand, D. B. Disease frequencies in dairy
cows in Sweden. V. Tramped Teat. Preventive Veterinary Medicine, 6; 1988b; 17–25.
Bergsten, C. Haemorrhages of the sole horn of dairy cows as a retrospective indicator
of laminitis: an epidemiological study. Acta Veterinaria Scandinavica, 35; 1994; 55–66.
Bergsten, C. Digital disorders in dairy cattle with special reference to laminitis and
heel horn erosion: the influence of housing, management and nutrition. Dissertation, Skara,
Sweden; 1995.
Bergsten, C. Effects of conformation and management system on hoof and leg diseases
and lameness in dairy cows. Veterinary Clinics of North America, Food Animal Practice, 17;
2001; 1–23.
Bergsten, C., Frank, B. Sole haemorrhages in tied primiparous cows as an indicator of
periparturient laminitis: Effects of diet, flooring and season. Acta Veterinaria Scandinavica,
37; 1996; 383–394.
Bergsten, C., Herlin, A. H. Sole haemorrhages and heel horn erosion in dairy cows:
The influence of housing system on their prevalence and severity. Acta Veterinaria
Scandinavica, 37; 1996; 395–408.
Bickert, W. G., Radostits, O. M. Housing and environment for dairy cattle. Radostits,
O. M. (ed.): Herd Health. Food Animal Production Medicine, 3rd Edition, W. B. Saunders
Company, A Harcourt Health Sciences Company, Philadelphia, U.S.A.; 2001.
Bruun, J., Ersb•ll, A. K., Alban, L. Risk factors for metritis in Danish dairy cows.
Preventive Veterinary Medicine, 54; 2002; 179–190.
Busato, A., Trachsel, P., Blum, J. W. Frequency of traumatic cow injuries in relation to
housing systems in Swiss organic dairy herds. Journal of Veterinary Medicine Series A Physiology, Pathology, Clinical Medicine, 47; 2000; 221–229.
DeGraves, F. J., Fetrow, J. Economics of mastitis and mastitis control. Veterinary
Clinics of North America: update on bovine mastitis, 9; 1993; 421–434.
Deluyker, H. A., Gay, J. M., Weaver, L. D. Interrelationships of somatic cell count,
mastitis and milk yield in a low somatic cell count herd. Journal of Dairy Science, 76; 1993;
3445–3452.
Diesch, S. L. Development and application of animal health information systems.
Proceedings of the 6th International Congress on Animal Hygiene, 14–17 June, Skara,
Sweden, 1988; 185–189.
Dijkhuizen, A. A., Morris, R. S. Animal health economics. Principles and applications.
Post Graduate Foundation of Veterinary Science, University of Sydney, Sydney, Australia;
1997.
Dohoo, I. R., Martin, S. W. Disease, production and culling in Holstein-Friesian cows.
III. Disease and production as determinants of disease. Preventive Veterinary Medicine, 2;
1984; 671–690.
Dohoo, I. R., Meek, A. H., Martin, S. W. Somatic cell counts in bovine milk,
relationship to production and clinical episodes of mastitis. Canadian Journal of Comparative
Medicine, 48; 1984a; 130–135.
Dohoo, I. R., Martin, S. W., Meek, A. H. Disease, production and culling in Holstein-Friesian
cows. VI. Effects of management on disease rates. Preventive Veterinary Medicine, 3; 1984b;
15–28.
Ekesbo. I. Health and welfare of farm animals and their impact on the livestock
industry. Proceedings of 6th WAAP World Conference of Animal Production, Helsinki,
Finland, 1988; 102–111.
Ekesbo, I. Kompendium i husdjurshygien. Del I, Department of Animal Hygiene, SLU,
Skara; 1991.
Ekesbo, I., Oltenacu, P. A. A dairy herd disease surveillance model based on farm
reports. Proceedings of 8th International Congress on Animal Hygiene. St. Paul, Minnesota,
USA, 1994; 21–24.
Ekesbo, I., Oltenacu, P. A., Vilson, B., Nilson, J. A disease monitoring system for
dairy herds. The Veterinary Record, 134; 1994; 270–273.
Elbers, A. R., Miltenburg, J. D., De Lange, D., Crauwels, A. P. Barkema, H. W.,
Schukken, Y. H. Risk factors for clinical mastitis in a random sample of dairy herds from the
southern part of The Netherlands. Journal of Dairy Science, 81; 1998; 420–426.
Ekman, T. A study of dairy herds with constantly low or constantly high bulk milk
somatic cell count – with special emphasis on management. Doctoral Dissertation. Acta
Universitatis Agriculturae Sueciae, Veterinaria 32, Uppsala, SLU; 1998.
Faye, B., Lescourret, F. Environmental factors associated with lameness in dairy cattle.
Preventive Veterinary Medicine, 7; 1989; 267–268.
Faye, B., Lescourret, F., Dorr, N., Tillard, E., MacDermott, B., McDermott, J.
Interrelationships between herd management practices and udder health status using canonical
correspondence analysis. Preventive Veterinary Medicine, 32; 1997; 171–190.
Frei, C., Frei, P. P., Stärk, K. D. C., Pfeiffer, D. U. & Kihm, U. The production system
and disease incidence in a national random longitudinal study of Swiss dairy herds. Preventive
Veterinary Medicine, 32; 1997; 1–21.
Gröhn, Y. T., Bruss, M. L. Effect of diseases, production and season on traumatic
reticuloperitonitis and ruminal acidosis in dairy cattle. Journal of Dairy Science, 73; 1990;
2355–2363.
Gröhn, Y. T., Rajala-Schultz, P. J. Epidemiology of reproductive performance in dairy
cows. Animal Reproduction Science, 60–61; 2000; 605–614.
Guard, C. Animal welfare and claw diseases. Proceedings of the 13th International
Symposium and 5th Conferencde on Lameness in Ruminants. Maribor, Slovenia, 2004, p.
155-158.
Gustafsson, A. H., Andersson, L., Emanuelson, U. Influence of feeding management,
concentrate intake and energy intake on the risk of hyperketonemia in Swedish Dairy herds.
Preventive Veterinary Medicine, 22; 1995; 237–248.
Fetrow, J., Mann, D. Production losses from mastitis: Carry over from the previous
lactation. Journal of Dairy Science, 74; 1991; 833–839.
Hamann, J. Trends in yield and health parameters: an attempt of a retrospective
analysis. Proceedings of the International Symposium “Prospects of Future Dairying: A
Challenge for Science and Industry”, 13–14 June, 1994, Tumba, Sweden, 1995; 57–61.
Hartung, J. Environment and Animal Health. Wathers, C. M. & Charles, D. R. (eds.):
Livestock Housing. CAB International, Wallingford, 1994.
Houe, H., •stergaard, S., Thilsing-Hansen, T., Jörgensen, R. J., Larsen, T., Sörensen,
J. T., Agger, J. F., Blom, J. Y. Milk fever and subclinical hypocalcaemia – an evaluation of
parameters on incidence risk, diagnosis, risk factors and biological effects as input for a
decision support system for disease control. Acta Veterinaria Scandinavica, 42; 2001; 3–29.
Hultgren, J. Foot/leg and udder health in relation to housing changes in Swedish dairy
herds. Preventive Veterinary Medicine, 53; 2002; 167–189.
Jones, G. M., Pearson, R. E., Clabaugh, G. A., Heald, C. W. Relationships between
somatic cell counts and milk production. Journal of Dairy Science, 67; 1984; 1823–1831.
Kossaibati, M. A., Hovi, M. & Esslemont, R. J. Incidence of clinical mastitis in dairy herds in
England. The Veterinary Record, 143; 1998; 649–653.
Kaneene, J. B., Miller R. Epidemiological study of metritis in Michigan dairy cattle.
Veterinary Research, 25; 1994; 253–257.
Koskiniemi, K. Observations on the incidence of teat injuries in different cowsheds.
Nordic Veterinary Medicine, 34; 1982; 13–19.
Matzke, P., Holzer, A., Deneke, J. The effect of environmental factors on the
occurrence of udder diseases. Tierarztliche Praxis, 20; 1992; 21–32.
Menzies, F. D., Mackie, D. P. Peer reviewed – Bovine toxic mastitis: risk factors and
control measures. Irish Veterinary Journal, 54; 2001; 30–37.
Morse, D., DeLorenzo, M. A., Wilcox, C. J., Natzke, R. P., Bray, D. R. Occurrence
and reoccurrence of clinical mastitis. Journal of Dairy Science, 70; 1987; 2168–2175.
Morse, D., DeLorenzo, M. A., Wilcox, C. J., Collier, R. J., Natzke, R. P., Bray, D. R.
Climatic effects on occurrence of clinical mastitis. Journal of Dairy Science, 71; 1988; 848–
853.
Natzke, R. P., Everett, R. W., Guthrie, R. S., Keown, J. F., Meek, A. M., Merril, W.
G., Roberts, S. J. & Schmidt, G. H. Mastitis control program: Effect on milk production.
Journal of Dairy Science, 55; 1972; 1256–1260.
Noordhuizen, J.P.T.M., Frankena, K., Thrusfield, M.V., Graat, E.A.M. Application of
Quantitative Methods in Veterinary Epidemiology. Wageningen Pers, 2001, 429 pp.
Noordhuizen, J.P., Collins, J.D. Pre-harvest health and quality monitoring, risk
assessment and their relevance to the food chain. Food safety assurance in the pre-harvest
phase.Wageningen Academic Publishers, The Netherlands, 2002, p. 115-124.
Näsi, M., Saloniemi, H. Effect of environmental change on injuries of udder and legs
in dairy cows. Nordic Veterinary Medicine, 33; 1981; 185–193.
Oltenacu, P., Bendixen, P. H., Vilson, B., Ekesbo, I. Tramped teats – clinical mastitis
disease complex in tied cows. Environmental risk factors and interrelationships with other
diseases. Acta Veterinaria Scandinavica, 31; 1990; 471–478.
Østerås O., Leslie, K. Animal housing and management – prevention of bovine
diseases. Proceedings of 9th International Congress in Animal Hygiene, 17–21 August,
Helsinki, Finland, 1997; 15–27.
Østerås O. Is all loose housing system equal good? Buskap og Avdrott, 1994; 10–11.
Philipot, J. M., Pluvinage, P., Cimarosti, I., Sulpice, P., Bugnard, F. Risk factors of
dairy cow lameness associated with housing conditions. Veterinary Research, 25; 1994; 244–
248.
Peeler, E. J., Green, M. J., Fitzpatrick, J. L., Morgan, K. L., Green, L. E. Risk factors
associated with clinical mastitis in low somatic cell count British dairy herds. Journal of Dairy
Science, 83; 2000; 2464–2472.
Rohrbach, B. W., Cannedy, A. L., Freeman, K., Slenning, B. D. Risk factors for
abomasal displacement in dairy cows. Journal of American Veterinary Medicine Association,
214; 1999; 1660–1663.
Rowlands, G. J., Russell, A. M., Williams, L. A. Effects of season, herd size,
management system and veterinary practice on the lameness incidence in dairy cattle. The
Veterinary Record, 113; 1983; 441–445.
Saloniemi, H. Udder diseases in dairy cows – field of observations on incidence,
somatic and environmental factors and control. Journal of the Scientific Agricultural Society
of Finland, Helsinki, 52; 1980; 85–184.
Saloniemi, H., Näsi, M. Effects of environmental change on udder health of dairy
cows. Nordic Veterinary Medicine, 33; 1981; 178–184.
Saloniemi, H., Roine, K. Field observations on the incidence of bovine clinical
mastitis and teat diseases. Nordic Veterinary Medicine, 33; 1981; 297–305.
Saloniemi, H., Gröhn, Y., Syväjärvi, J. An epidemiological and genetic study on
registered diseases in Finnish Ayrshire cattle. II. Reproductive disorders. Acta Veterinaria
Scandinavica, 27; 1986; 196–208.
Saloniemi, H. Piimalehmade tervise kontrolli süsteem Soomes. Eesti Loomaarstlik
Ringvaade, 18; 1991; 14–19.
Saloniemi, H. Keskkonnategurite mõju udarahaiguste sagedusele. Sandholm, M.,
Honkanen-Buzalski, T., Kaartinen, L., Pyörälä, S. (koostajad). Lehma udar ja udarahaigused.
ELÜ kirjastus, Tartu, 1996; 222–227.
Scaife, J.R., Galbraith, H., Bergsten, Ch., Green, L.E., Mülling, Ch.K.W., Pijl, R.,
Stanek, Ch., Urbaniak, K. Lamecow 2002-2006. A multidistsiplinary approach to the
reduction in lameness and improvement in dairy cow welfare in the European Community.
Proceedings of the 13th International Symposium and 5th Conferencde on Lameness in
Ruminants. Maribor, Slovenia, 2004, p. 158-160.
Schukken, Y. H., Grommers, F. J., Van de Geer, D., Erb, H. N. & Brand, A. Risk
factors for clinical mastitis in herds with a low bulk milk somatic cell count. 2. Risk factors
for Escherichia coli and Staphylococcus aureus. Journal of Dairy Science, 74; 1991; 826–832.
Swedish Dairy Association. Djurhälsovård 1999/2000. Redogörelse för
husdjursorganisationens djurhälsovård. Stockholm, Report; 2001.
Sviland, S., Waage, S. Clinical bovine mastitis in Norway. Preventive Veterinary
Medicine, 54; 2002; 65–78.
Thrusfield, M. veterinary Epidemiology. Blackwell Science, 2001, 483 pp.
Thysen, I. Foot and leg disorders in dairy cattle in different housing systems.
Wierenga, H. K., Peterse, D. J. (ed.): Cattle housing systems, lameness and behaviuor. Current
Topics in Veterinary Medicine and Animal Science, Martinus Nijhoff Publishers for CEC,
Dordrecht, The Netherlands, 1987; 166–178.
Waage, S. Epidemiological studies on hypomagnesaemia in cattle. Proceedings and
Abstracts of the 17th Nordic Veterinary Congress, July 26–29, Reikjavik, Iceland, 1994; 170.
Vannier, P., Tillon, J. P., Madec, F., Morisse, J. P. Environment and gastro-enteritis.
Annales de Recherches Veterinaires, 14; 1983; 450–455.
Valde, J. P., Hird, D. W., Thurmond, M. C., •sterås, O. Comparison of ketosis,
clinical mastitis, somatic cell count, and reproductive performance between free stall and tie
stall barns in Norwegian dairy herds with automatic feeding. Acta Veterinaria Scandinavica,
38; 1997; 181–192.
Waldner, C. Investigation of disease outbreaks and suboptimum productivity in herds.
Radostits, O. M. (ed.): Herd Health. Food Animal Production Medicine, 3rd Edition, W. B.
Saunders Company, A Harcourt Health Sciences Company, Philadelphia, U.S.A.; 2001.
Weary, D. M., Taszkun, I. Hock lesions and free-stall design. Journal of Dairy Science,
83; 2000; 697–702.
Vermunt, J. Herd lameness-a review, major causal factors, and guidelines for
prevention and control. Proceedings of the 13th International Symposium and 5th
Conferencde on Lameness in Ruminants. Maribor, Slovenia, 2004, p. 3-17.
Whitaker, D. A., Kelly, J. M., Smith, S. Disposal and disease rates in 340 British dairy
herds. The Veterinary Record, 146; 2000; 363–367.
Willesmith, J. W., Francis, P. G., Wilson, C. D. Incidence of clinical mastitis in a
cohort of British dairy herds. The Veterinary Record, 118; 1986; 199–204.
Recent findings
Health monitoring model for a herd of milking cows and its application for health
evaluation and improvement
[E-A 12]
Aims of study
1. To determine the incidence rate of multifactorial diseases in Estonian dairy herds.
2. To determine the risk factors for multifactorial diseases and their hierarhy in connection with
housing conditions in cowsheds for the Estonian dairy herds.
Material and methods
The research involved 33 dairy herd cowsheds and roughly 5000 dairy cows all over Estonia. A
total of 87332 observations or cow-months (the number of cows that underwent sample milking
every month + sick dry cows during the experimental period) were gathered in a database.
Data concerning housing conditions (housing system, microclimate, placement of animals, stalls,
mangers etc.), management routines (feeding, manure handling and milking technologies etc.),
the technical and hygienic status of the cowsheds and microclimate (temperature, relative
humidity, air velocity and ammonia concentration) were annually registered during three seasonal
visits. Production data were obtained from the Animal Recording Centre. Diseases were
diagnosed and registered by the local veterinarians.
From the collected data, four databases were established: 1) diseases; 2) microclimate; 3)
facilities and 4) milk production.
For the analysis of environmental factors as risk factors single and integrated mathematical
models were used constructed on the basis of standard regression and logistic regression
methods.
In order to compare the influence of risk factors (for the presentation of hierarchy of influence),
the concept of the risk factor index was adopted. The risk factor index AI describes the given
factor’s cumulative influence on all disease cases.
The following procedures are performed to determine AI :
1) disease groups for which the given factor proved to be a risk factor with 95% confidence are
determined;
2) the intensity of the influence of the risk factor on disease group is determined, equating them
with the relative frequency of that group of diseases out of all disease cases (the method is
indirect, although it has been adopted in this stage due to the absence of a better alternative);
3. the relative frequency of these disease groups are added in the general distribution of diseases
for which this factor proved to be a risk factor.
Mathematically, these procedures are expressed using the formula
Ai   Ki hi ,
where Ki denotes the relative frequency of disease i cases out of all cases and hi is the
influence of the given factor on disease incidence I (1 - acts as a risk factor; 0 - does not act as
a risk factor).
Results
Disease incidence in Estonian dairy cows
The results of the disease incidence are presented in table 1.
Table 1. Disease incidence in Estonian dairy cows
Disease or disease group
Udder diseases
Uterine infection
Metabolic diseases
Disease incidence
4708
2389
1190
Incidence rate (%)
5.39
2.74
1.36
95% CI
5.37–5.41
2.73–2.75
1.35–1.37
Retained placenta
Foot diseases
Other injuries
Enteritis
Disorders of rumen or abomasum
Ovulatory dysfunction
Dystocia
Abortion
Prolapse of uterus
Skin diseases
Diseases of respiratory tract
TOTAL
751
349
207
164
140
137
129
50
52
29
17
10312
0.86
0.40
0.24
0.19
0.16
0.15
0.15
0.06
0.06
0.03
0.02
11.81
0.85–0.87
0.40–0.40
0.24–0.24
0.19–0.19
0.16–0.16
0.15–0.15
0.15–0.15
0.06–0.06
0.06–0.06
0.03–0.03
0.02–0.02
11.78–11.82
The panorama of multifactorial diseases in Estonian dairy cows is given in Figure 1. The most
common diseases of dairy cows in Estonia are udder diseases (45.7%), uterine infection (23.2%),
metabolic diseases (11.5%), retained placenta (7.3%) followed by foot diseases (3.4%), other
injuries (2.0%), enteritis (1.6%), disorders of rumen or abomasum (1.4%), ovulatory dysfunction
(1.3%) and dystocia (1.3%). Relatively fewer cases were registered on abortion (0.5%), prolapse
of the uterus (0.5%), skin diseases (0.3%) and diseases of the respiratory tract (0.2%). As the
relative frequency of abortion (0.5%), skin diseases (0.3%) and diseases of the respiratory tract
(0.2%) was very low, these diseases were not included into the analysis of risk factors.
Figure 1. The panorama of multifactorial diseases in Estonian dairy cows
Uterine infection
23.2%
Metabolic diseases
11.5%
Retained placenta
7.3%
Foot diseases
3.4%
Other injuries
2.0%
Enteritis
1.6%
Disorders of rumen or
abomasum
1.4%
Ovulatory dysfunction
1.3%
Abortion
0.5%
Udder diseases
45.7%
Dystocia
1.3%
Prolapse of uterus
0.5%
Diseases of respiratorySkin diseases
tract
0.3%
0.2%
Single analysis of risk factors
[E-A 13]
The results of the influence of risk factors on the udder diseases incidence are presented in table
2 as an example. With similar analyses risk factors for other disease groups were estimated.
Table 2. Udder diseases. Incidence and relative risk by risk factors
Risk factor
Manure removal
Manual
Scraper
Tractor
Type of bedding
Straw
Peat
Sawdust
Amount of bedding
Plenty
Medium
Little
Stall partitions
on both sides
on one side
no partitions
Stall length
Stall width
Manger width
Height of manger edge
Air velocity
Milk production
Number of
cases
Incidence
rate (%)
Relative
risk
95% CI
12
1548
3148
1.40
4.95
5.70
1
3.54
4.07
2.01–6.24
2.31–7.17
540
3156
1012
3.49
6.18
4.86
1
1.77
1.39
1.62–1.94
1.25–1.54
345
1744
2619
3.39
4.55
6.75
1
1.34
1.99
1.19–1.50
1.78–2.23
577
576
3555
4.39
5.75
5.54
1
1.31
1.26
1.03
0.96
0.99
0.99
2.00
1.07
1.17–1.47
1.15–1.38
1.03–1.03
0.96–0.97
0.99–0.99
0.99–1.00
1.65–2.42
1.06–1.07
The risk factors of udder diseases were:
- removal of manure with scraper or tractor in comparison with manual removing,
- the use of peat and sawdust as bedding material in comparison with straw,
- medium and limited amount of bedding,
- the absence of stall partitions or location only on one side,
- long and narrow stall,
- narrow manger with low edge,
- increased air velocity,
- higher milk productivity.
The risk factors of uterine infection were: [E-A 14]
- removal of manure with scraper or tractor in comparison with manual removing,
- the use of peat and sawdust as bedding material in comparison with straw,
- medium and limited amount of bedding,
- the absence of stall partitions or location only on one side,
- short and narrow stall,
- manger with higher edge and bottom,
- higher milk productivity.
The risk factors of metabolic diseases were:
[E-A 15]
- worse hygienic conditions (worse status of the cowshed and strong smell),
- winter and spring as compared to autumn,
- low bottom of manger,
- higher air temperature,
- higher milk productivity.
The risk factors of retained placenta were:
[E-A 16]
- worse hygienic conditions (worse status of the cowshed),
- the use of peat and sawdust as bedding material in comparison with straw,
- medium and limited amount of bedding,
- spring,
- low bottom of manger,
- higher milk productivity.
The risk factors of foot diseases were:
[E-A 17]
- using straw as bedding material in comparison with peat and sawdust,
- stall partitions located on one or both sides,
- longer stall,
- autumn,
- increased air velocity and humidity,
- higher production.
The risk factors of other injuries were:
- peat and sawdust as a bedding material (in comparison with straw),
- smaller amount of bedding,
- stall partitions on both sides,
- longer stall length,
- narrow manger,
- higher milk production.
In case of enteritis the next factors operated as risk factors:
- sawdust as a bedding material,
- smaller amount of bedding,
- spring,
- lower air temperature and velocity,
- higher air humidity,
- higher milk production.
[E-A 18]
The risk of disorders of rumen and abomasum increased in winter and spring.
The risk factors of ovulatory dysfunction were: [E-A 19]
- lower hygiene level in the cowshed (worse status of cowshed and strong smell),
- stall partitions on one or both sides,
- winter,
- lower temperature and high air humidity.
The risk factors of dystocia were: [E-A 20]
- lower hygienic level (status of cowshed satisfactory, strong smell, lower temperature, higher
ammonia content),
- stall partitions on one or both sides,
- lower bottom of manger,
- winter and spring.
The occurrence of prolapse of the uteri was mainly influenced by the season,
being more frequent in winter and spring.
Assessment of influence of risk factors on the basis of complex model
The analysis of diseases with complex models emphasised or confirmed the effect of seven risk
factors (stall partitions, stall length and width, manger width and the height of manger edge, air
velocity and milk production) on udder diseases; the effect of six risk factors (type and amount of
bedding, stall length and width, the height of manger edge and milk production) on uterine
infection; the effect of five risk factors (season, smell intensity, the height of manger, air
temperature and milk production) on metabolic diseases; the effect of three risk factors (air
humidity content, air velocity and milk production) on foot diseases; the effect of four risk
factors (stall partitions, stall length, manger width and milk production) on other injuries and the
effect of one risk factor (air velocity) on the increased risk of enteritis.
The adjusted relative risks (odds ratio, relative odds) of many risk factors do not, however,
adequately reflect the strong mutual interdependence of the risk factors or their similar influence.
Thus some of the factors that have not been confirmed by this analysis may nevertheless prove to
be risk factors increasing disease incidence. Additional research must be performed in order to
achieve a conclusive answer to this question.
Comparative analysis of risk factors
[E-A 21]
On the basis of the indexes of the analysed risk factors, the following influence hierarchy was
prepared.
Environmental risk factors
1. Type of housing (0.845)
2. Type of bedding (0.832)
3. Amount of bedding (0.798)
4. Stall partitions (0.769)
5. Length of stall (0.743)
6. Width of stall (0.689)
7. Height of manger edge (0.689)
8. Manure removal (0.689)
9. Air velocity (0.507)
10. Width of manger (0.477)
11. Height of manger from the stall level (0.433)
12. Season (0.283)
13. Overall status of the cowshed (0.214)
14. Air temperature (0.157)
15. Smell intensity (0.141)
16. Air humidity content (0.063)
17. Ammonia content in the air (0.013)
Individual risk factors
1. Milk production (0.947)
2. Breed (0.427)
More than 80% of the disease cases are connected with housing type, which consists of the effect
of many individual factors. The most significant environmental risk factors, influencing over
75% of disease cases, appeared to be the type and amount of bedding and stall partitions. Stall
length and width, the height of manger edge, manure removal and air velocity increase the risk of
50–75% of disease incidences. Manger width and height from the stall level, season, the overall
status of the cowshed, air temperature, smell intensity, air humidity and ammonia content
increase disease incidence by less than 50%.
Milk production as an individual risk factor increases the risk of most of the more frequent
diseases, whereas breed is a risk factor for less than 50% of disease cases.
Conclusions
1. The most frequent diseases of the Estonian dairy cows are udder diseases, followed by uterine
infection, metabolic diseases and retained placenta. Disease incidence in Estonian dairy herds
is similar to that of other European countries.
2. Of the technological factors characterising dairy cows’ housing environment, stall partitions,
stall length and manger design have the greatest influence on the disease incidence. Of factors
pertaining to the sanitary condition of the cowsheds, the type and amount of bedding are the
most significant. Air temperature and velocity - these two microclimatic factors have the
greatest influence on disease incidence. The loose housing of dairy cows has a series of
benefits over the tied housing of dairy cows. Thus the trend of replacing tied housing with
loose housing is justified from the point of view of animals’ health.
Health monitoring model for a herd of milking cows (description)
Basic epidemiological measures used in summarising animals’ health
monitoring data [E-A 22]
The disease incidence is defined as number of new cases of illness commencing, or of
persons falling ill, during a specified time period in a given population. In animal
husbandry, where the animals disease status is usually monitored during long time period
and one observation corresponds to the animal’s disease status in unit period, the disease
incidence can be defined also as the number of observations with disease.
For example the results about disease incidences in Estonian dairy cows are presented in
Table 1. Note, that here the total number of disease incidents does not mean the number
of different diseased cows, but this number shows the number of months where the cows
had a certain disease summed over whole time period and studied farms.
Table 1. Disease incidence
Disease or disease group
Udder diseases
Uterine infection
Metabolic diseases
Retained placenta
Foot diseases
Other injuries
Enteritis
Disorders of rumen or abomasum
Ovulatory dysfunction
Dystocia
Abortion
Prolapse of uterus
Skin diseases
Diseases of respiratory tract
TOTAL
Disease
incidence
4708
2389
1190
751
349
207
164
140
137
129
50
52
29
17
10312
Based on disease incidences the proportions of certain diseases in whole number of
disease incidents can be found.
For example the panorama of multifactorial diseases in Estonian dairy cows is given in
Figure 1. The most common diseases of dairy cows in Estonia are udder diseases
(45.7%), uterine infection (23.2%), metabolic diseases (11.5%), retained placenta (7.3%)
followed by foot diseases (3.0%), other injuries (2.0%), enteritis (1.6%), disorders of
rumen or abomasum (1.4%), ovulatory dysfunction (1.3%) and dystocia (1.3%).
Relatively fewer cases were registered on abortion (0.5%), prolapse of the uterus (0.5%),
skin diseases (0.3%) and diseases of the respiratory tract (0.2%).
Figure 1. The panorama of multifactorial diseases in Estonian dairy cows
Uterine infection
23.2%
Metabolic diseases
11.5%
Retained placenta
7.3%
Foot diseases
3.4%
Other injuries
2.0%
Enteritis
1.6%
Disorders of rumen
or abomasum
1.4%
Ovulatory
dysfunction
1.3%
Abortion
0.5%
Udder diseases
45.7%
Diseases of
respiratory tract
0.2%
Dystocia
1.3%
Prolapse of uterus
0.5%
Skin diseases
0.3%
The prevalence rate (PR) is defined as the proportion of diseased animals in fixed time
moment or period to population size in that moment or period.
The incidence rate (IR) is defined as the proportion of new cases of illness commencing
during a specified time period in a given population to the population at risk (the total
number of observations).
The estimate of where the true value of a result lies is usually expressed in terms of a
95% confidence interval (CI), or confidence limits. The calculation of confidence limits
bases on the (asymptotic) distribution of studied characteristic. In case of large sample,
usually the normal distribution is used to get approximate confidence intervals.
For incidence rate the asymptotic confidence limits can be found using the following
formula:
95% CIIR  IR 1.96 IR (number of observations) .
For example, the disease incidences, incidence rates in percents (multiplied with 100%)
and the confidence intervals of incidence rates in Estonian milking cow’s study are
presented in Table 2. The total number of observations was 87332.
Table 2. Disease incidences in Estonian dairy cows (n = 87332)
Disease or disease group
Udder diseases
Uterine infection
Metabolic diseases
Retained placenta
Foot diseases
Other injuries
Enteritis
Disorders of rumen or abomasum
Ovulatory dysfunction
Dystocia
Abortion
Prolapse of uterus
Skin diseases
Diseases of respiratory tract
TOTAL
Disease
incidence
4708
2389
1190
751
349
207
164
140
137
129
50
52
29
17
10312
Incidence rate
(%)
5.39
2.74
1.36
0.86
0.40
0.24
0.19
0.16
0.15
0.15
0.06
0.06
0.03
0.02
11.81
95% CI
5.37–5.41
2.73–2.75
1.35–1.37
0.85–0.87
0.40–0.40
0.24–0.24
0.19–0.19
0.16–0.16
0.15–0.15
0.15–0.15
0.06–0.06
0.06–0.06
0.03–0.03
0.02–0.02
11.78–11.82
To compare the disease status in different groups the measure called as relative risk (RR)
is used. The relative risk is defined as the ratio of the probability of developing, in a
specified period of time, an outcome among those receiving the treatment of interest or
exposed to a risk factor, compared with the probability of developing the outcome if the
risk factor or intervention is not present. The RR can be calculated as the ratio of
incidence rates.
For example, comparing the keeping conditions in Estonian milking cow’s study, there
were in total 6600 observations with free stall keeping and 80732 observations with tie
keeping. There were registered 190 and 4518 udder diseases, respectively in case of free
stall keeping and tie keeping. The corresponding incidence rates are 190/ 6600  0.0288
and 4518/ 80732  0.0560 . The risk for cow to get an udder disease in case of tie
keeping compared to free stall keeping is estimated as 0.0560/ 0.0288  1.94 .
For relative risk the asymptotic confidence limits can be found using the following
formula:
95% CIRR  eln(RR)1.96se[ln(RR)] 
e
RR
1.96se[ln(RR)]

; RR  e1.96se[ln(RR)] ,
where ln is the natural logarithm, e is the known constant (e = 2.71828… );
se[ln(RR)]

1
1

number of cases in exposed animals number of cases in non-exposed animals
and se denotes the standard error.
For example, comparing the keeping conditions in Estonian milking cow’s udder diseases
study, the 95% confidence limits for RR are approximately calculated as
95% CI RR 
e
1.94
1.96 1 190 1 4518
;1.94  e1.96
1 190 1 4518
  1.68; 2.24 .
As this interval does not include 1, then there is less than a 1 in 20 chance that the
reported difference between keeping conditions is solely due to chance.
If the risk factor has more than two levels, then the relative risks can be calculated in relation to the
different levels, usually the level of risk factor with the lowest incidence rate is used as the base.
For example, the udder diseases incidences, incidence rates, relative risks and the
confidence intervals of relative risks in case of different dung removal methods and in
case of different types of bedding in Estonian milking cow’s study are presented in Table
3.
Table 3. Udder diseases – incidence and relative risks by risk factors in Estonian
dairy cows
Risk factor
Dung removal
manual
scraper
tractor
Type of bedding
straw
peat
sawdust
Number of Number of cases Incidence rate
observations
Relative risk
95% CI
848
29735
52041
12
1548
3148
0.014
0.050
0.057
1.00
3.54
4.07
2.01–6.25
2.31–7.17
14952
47879
19793
540
3156
1012
0.035
0.062
0.049
1.00
1.77
1.39
1.62–1.94
1.25–1.54
Other commonly used disease status measures in epidemiological studies are odds and
odds ratios. The odds of an event are calculated as the number of events divided by the
number of non-events.
For example, on average 2000 drones are born in every 60000 births in beehive during year, so the
odds of any randomly chosen bee being that of a drone is:
number of drones number of queens  2000 58000  0.034 .
Equivalently we could have calculated the same answer as the ratio of the bee being a
drone (0.033) and it not being a drone (0.967). If the odds of an event are greater than one
the event is more likely to happen than not; if the odds are less than one the chances are
that the event won't happen.
When events are rare, risks and odds are very similar. For example, in the bee’s sex
example 2000 of 60000 born bees were drones: a risk of 0.033 [2000/60000] or an odds
of 0.034 [2000/(60000-2000)].
Odds ratio (OR; synonyms: cross-product ratio, relative odds) is the probability of the
event divided by the probability of the nonevent. It is a measure of the degree of
association – for example, the odds of exposure among the cases (receiving the treatment
of interest or exposed to a risk factor) compared with the odds of exposure among the
controls (the risk factor or intervention is not present).
For odds ratio the asymptotic confidence limits can be found using the following formula:
95% CIOR  eln(OR)1.96se[ln(OR)] 
e
OR
1.96se[ln(OR)]

;OR  e1.96se[ln(OR)] ,
where
se[ln(OR)] 
1
number of cases in
exposed animals

1
number of cases in
non-exposed animals

1
number of controls in
exposed animals

1
number of controls in
non-exposed animals
.
When (disease) events are rare (which is usual in veterinary medicine), the estimates of
RR are similar to those of OR.
For example, comparing the keeping conditions in Estonian milking cow’s udder diseases
study, the OR and its approximated 95% CI are calculated as
OR 
95% CIOR 
e
4518
190
 0.0593  2.00 ,
(80732  4518) (6600  190) 0.0296
2.00
1.96 1 190 1 45181 6410 1 76214
; 2.00  e1.96
1 190 1 45181 6410 1 76214
  1.73; 2.32 .
This suggests that those cows who are kept in tie keeping conditions, are almost 2 times
more likely diseased in udder diseases than those who are living in farms with free stall
keeping.
Similarly to the relative risk, in case of risk factors with more than two levels, the odds
ratios can be calculated in relation to the different levels.
Odds ratios are the main parameters used in hypothesis testing and model building in
epidemiological studies.
Epidemiological studies generally try to identify factors that cause harm – those with odds
ratios greater than one (contrary to clinical trials, where typically is looked for treatments
which reduce event rates, and which have odds ratios of less than one). For example, the
tie keeping can cause more udder diseases compared with free stall keeping.
The “logit” model
The "logit" model is used instead of standard regression and analysis of variance
(ANOVA) models, if the dependent variable is binary and is measured on the 0/1-scale.
For example the disease status (healthy/diseased), pregnancy status, treatment effect
(no/yes).
The logistic regression model has a form
logit( )  ln[ (1   )]     x   ,
or
 (1   )  e   x ,
where ln is the natural logarithm, e is the known constant (e = 2.71828… );  is the
probability that the studied event occurs, for example, the animal is diseased;  (1   ) is
the odds ratio and ln[ (1   )] is the log odds ratio, or “logit”; x is the independent
variable (argument); ,  and  are respectively the regression coefficients and random
error term, like in standard regression analyses.
The logistic regression model is simply a non-linear transformation of the linear regression. The
"logistic" distribution is an S-shaped distribution function, which constrains the estimated
probabilities to lie between 0 and 1. From the logistic regression model the estimated probability is
expressed as:
   x
  e    x .
1 e
Now it is evident, that if you let    x  0 , then   0.5 ; as    x gets really big, 
approaches 1; and as    x gets really small,  approaches 0.
For example, assuming that all observations in Estonian milking cow’s study are
independent, then the udder diseases incidence (  ) is predictable by stall width (SW)
with simple logistic regression model of the form
1.5900.038*SW
  e 1.5900.038*SW .
1 e
The graphical representation of last model is visible on Figure 2.
Figure 2. The udder diseases incidence in Estonian dairy cows predicted by stall
width
Udder disease incidence
0,13
0,11
0,09
0,07
0,05
0,03
0,01
90
100
110
120
130
140
Stall width
The exponent of regression coefficient  , e  , is interpreted as the change in odds ratio
corresponding to the one unit change in independent variable. For example, if e   2 ,
then a one unit change in independent variable would make the event twice as likely to
occur. Negative regression coefficients lead to odds ratios less than one: if e   1 , then a
one unit change in independent variable leads to the event being less likely to occur.
For example, in Estonian milking cow’s study the regression coefficient allowing to
predict the changes in udder disease incidences based on stall width, is -0.038. Thus the
odds ratio corresponding to the 1 cm increase in stall width is equal to e 0.038  0.96 ; the
odds ratio corresponding to the 10 cm increase in stall width is equal to e 0.038*10  0.68 .
Usually the logistic regression analysis is performed with help of statistical analysis programs (SAS,
R, SPSS, …) and the output contains additionally information about the exact confidence limits of
estimated parameters and p-values corresponding to the tests of parameters statistical significance. If
only confidence intervals to regression coefficients are printed out, then the confidence intervals to
odds ratios can be calculated by applying the exponent function to coefficient  CI’s.
The part of standard output of SAS procedure LOGISTIC is presented on Figure 3.
Figure 3. The part of standard output of SAS procedure LOGISTIC
The LOGISTIC Procedure
Analysis of Maximum Likelihood Estimates
Parameter
DF
Estimate
Standard
Error
Wald
Chi-Square
Pr > ChiSq
Intercept
ST_WIDTH
1
1
1.5902
-0.0381
0.3461
0.00297
21.1140
164.8480
<.0001
<.0001
Odds Ratio Estimates
Effect
ST_WIDTH
Point
Estimate
0.963
95% Wald
Confidence Limits
0.957
0.968
Since usually the investigated diseases are multifactorial, i.e. many different factors
participate in their aetiology, it is natural to analyse different risk factors in the context of
a single complex model, also taking into consideration possible confounding influences.
For this the generalized linear models with logistic link function can be used.
For example, in Estonian milking cow’s udder diseases study, the complex model of the
following form was used:
logit() =  + Ki + DRj + BTk + Fl + YMm + b1*SWijklmno + Ln + ijklmno,
where  is disease incidence,  is the intercept, Ki is the influence of housing type i, DRj is the
influence of manure removal j, BTk is the influence of type of bedding k, Fl is the influence of the
farm l, YMm is the influence of year-month combination m, SWijklmno is stall width and b1 is the
corresponding regression coefficient, Ln describes the effect of the repeated measurement of the nth
cow, and ijklmno designates the portion of the value of the investigated attribute that failed to be
described by the factors (random error).
From such models, where the possible confounding influences are taken into the consideration,
adjusted odds ratios (AOR, sometimes named also as adjusted relative risks) can be estimated by
applying the exponent function to the assessments of the parameters of the model issued by the
computer.
The part of standard output of SAS procedure GENMOD, used to fit the abovementioned model
with udder diseases data in Estonian milking cow’s study, is presented on Figure 4. From parameter
estimates table in Figure 4 the adjusted odds ratios and their confidence intervals can be calculated
and in last table the Wald Type 3 test results about factors significance are presented.
Figure 4. The part of standard output of SAS procedure GENMOD
Analysis Of GEE Parameter Estimates
Empirical Standard Error Estimates
Parameter
Estimate
Standard
Error
Intercept
4.5755
0.9276
95% Confidence
Limits
Z Pr > |Z|
2.7576
6.3935
4.93
<.0001
0.8111
0.0000
-2.0283
-1.6877
0.0000
-0.7648
0.0000
0.0000
-0.0766
1.4564
0.0000
-0.7211
-0.5120
0.0000
-0.4840
0.0000
0.0000
-0.0455
6.89
.
-4.12
-3.67
.
-8.72
.
.
-7.70
<.0001
.
<.0001
0.0002
.
<.0001
.
.
<.0001
……
KEEP
KEEP
BE_TYPE
BE_TYPE
BE_TYPE
DU_REM
DU_REM
DU_REM
ST_WIDTH
1
3
1
2
3
1
2
3
1.1338
0.0000
-1.3747
-1.0999
0.0000
-0.6244
0.0000
0.0000
-0.0611
0.1646
0.0000
0.3335
0.2999
0.0000
0.0716
0.0000
0.0000
0.0079
Wald Statistics For Type 3 GEE Analysis
Source
DF
ChiSquare
Pr > ChiSq
FARM
YEAR_MON
KEEP
BE_TYPE
DU_REM
ST_WIDTH
10
38
1
2
1
1
391.94
255.36
47.43
17.04
75.98
59.25
<.0001
<.0001
<.0001
0.0002
<.0001
<.0001