Zul Bahar Bin Abdul Rashid MVS Dissertation.

Zul Bahar Bin Abdul Rashid MVS Dissertation.
MVS Dissertation
MVS Dissertation
This dissertation reports the result from an investigation of spontaneous humeri fractures that
happened in New Zealand dairy cattle population between 2007 and 2012. As the syndrome
was relatively new in New Zealand and elsewhere, the case definition was derived from a
case series report in 2008.
Questionnaires were mailed to potential respondents whose farm suspected to have the
outcome of interest as recommended by various parties (veterinarians, researchers, farmers)
who had seen or knew farms, which had recorded the spontaneous fractures' syndrome.
A total of 149 cases was reported in the five-year observation period from 2007 to 2012 with
an increasing trend (r2=0.71) in 22 farms that responded to the study. Out of the 149 reported
incident of spontaneous fracture, 115 case details managed to be gathered and analysed. The
result showed that the spontaneous fracture syndrome exhibit a spatial clustering, which was
utilised to compare the persistence of identified risk factors in the different geographical
cluster. The spontaneous fracture syndrome also displayed an observable temporal pattern
whereby the occurrences were recorded in early spring, peaked in late spring and ended in
early summer in every observation year. All case animals were female, relatively young with
a noticeable biphasic age profile (24-31 months and 36-40 months), good body condition and
reproductively active.
As the fracture occurrences coincided with the period of high calcium demand, transient
osteoporosis to pregnancy and lactation was hypothesized to cause the spontaneous humeri
fractures in New Zealand dairy cattle population between 2007 and 2012. Other factors which
could be the risk factors based on the persistency in the presence prior, and at the time of
fractures were: lacked of dietary calcium in the growing stage, the breed of the dairy cows,
high-quality index (breeding and production worth), increased walk speed of the lactating
cows, and the involvement of a truck for heifer transfer from grazier to the case farm.
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I came to Massey two years ago with a pretext of learning useful skills that enable me
to discharge my duty better. It was not easy initially especially after hanging the student
jersey for almost 11 years. Several groups of people had a strong influence on me whom
without them; my journey in pursuing postgraduate study would be dull, monotonous and
I wish to thank the following academic staffs for patiently enriching my
epidemiological skills; Eric Newman, Jackie Benschop, Nigel French, Cord Heuer, Deb
Pratley, Naomi Cogger, Mark Stevenson, Daan Vink. This learning process would not be
smooth without the involvement of the following administration staffs; Christine
Cunningham, Simon Verschaffelt, Wendy Maharey, Mirjana Moffats, Debbie Hill.
I am forever in debt to my chief supervisor, Cord Heuer, who put me back into the
epidemiological discipline by inviting me to the spontaneous fracture investigation team, and
guiding me until this dissertation is produced. Special thanks are forwarded to: my
supervisor, Daan Vink, whose involvement in every step along the way (questionnaire
design, data analysis, and text editing), could never be disputed; my technical supervisor,
Jenny Weston, who was at the material time a board member of the Dairy Cattle Veterinary
Association (DCV), used the internal communications of DCV to disperse the news about the
study, made the earlier contact with the veterinarians, provided me with a list of possible
respondent and assisting me with the follow-up when the respondent refused to respond to
me. Without her, it could take forever to increase the response rate. Not forgetting Keith
Thompson and Karen Dittmer whose guidance assisted me in improving the questionnaire
and the final text. I would also like to acknowledge the involvement and assistance from
enthusiastic farmers who generously allocated their precious time to fill in the questionnaire;
and a handful of veterinarians who assisted me by providing the farm address and involved in
the follow-up activities. A few of the veterinarians actually went to the farms to collect the
information themselves!!! For the record, these fine veterinarians helped in the investigation:
Jenny Weston, April Goldsmith, Cecelia van Velsen, Anna Tarver, Hamish Newton, John
McCarthy, David Steward, Katie Denholm, Jan Meertens, Kate Sommerville, Noelle
Finlayson, Gerald Pinckney, Mary Lund Ben Hitchcock, Greig Hollway, Keven Lawrence,
and others who worked behind the scene.
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My course mates, who endured the ‘easy to understand lectures but excruciating
assignment tasks’, I wish to salute you for surviving the hurdles in one piece. Just remember
that calm sea would not produce a skilful sailor.
My dear office mates, Webby Chibomba, a brother I have never had from African
continent, you have been a very good friend for the past two years. I have spent more time
with you that anyone else in Epicentre just by sitting in the office for five hours a day, five
days a week. Thank you for your patient ears and prudent words. Indeed, you are more than
what an officemate could ask for.
I am grateful to the Department of Public Service, Sabah, East Malaysia for the
funding my study in Epicenter, Massey University. The funding will not be materialized
without the strong support and recommendation by the Director of the Department of
Veterinary Services and Animal Husbandry (Sabah, Malaysia) who foresees the potential of
epidemiology discipline in accelerating the development of animal industry in Sabah.
I really appreciate the encouragement received from my family members in Sabah,
Malaysia. Last but not least, I wish to thank my dearest wife Mera Hidayawati, sons
Zulkarnain and Zulkhairi, and my daughter Zulaikha for their willingness to leave their
comfort zone by accompanying me throughout my study. Their unconditional love and
patience keep me going no matter how hard it was.
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Table of content
Abstract ..................................................................................................................................... II
Acknowledgement ................................................................................................................... III
Table of content ........................................................................................................................ V
List of table ............................................................................................................................ VII
List of figure ......................................................................................................................... VIII
A general introduction to the bone biology and literature review ...................................... 1
Introduction ................................................................................................................. 1
Bone composition ........................................................................................................ 1
Bone cells ............................................................................................................. 2
Bone matrix .......................................................................................................... 3
Bone function .............................................................................................................. 1
Support function................................................................................................... 1
Protection function ............................................................................................... 2
Movement function .............................................................................................. 2
Blood cells production function ........................................................................... 2
Mineral storage function ...................................................................................... 3
Long bone growth ....................................................................................................... 3
Growth in flat bones .................................................................................................... 4
Bone remodelling ........................................................................................................ 5
Bone regulators ........................................................................................................... 6
Local regulators ................................................................................................... 6
Systemic regulators .............................................................................................. 7
Biomechanics of bone ............................................................................................... 10
Low force fracture ..................................................................................................... 13
Osteoporosis ....................................................................................................... 13
1.10 Conclusion................................................................................................................. 19
2 Spontaneous humeri fractures in New Zealand dairy population 2007-2012; a series of
115 cases .................................................................................................................................. 20
Introduction ............................................................................................................... 20
Objectives .................................................................................................................. 22
Materials and method ................................................................................................ 22
Study design ....................................................................................................... 22
The respondent ................................................................................................... 23
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The case definition ............................................................................................. 23
The questionnaire ............................................................................................... 24
Data handling and analysis ................................................................................ 24
Descriptive data analysis.................................................................................... 24
Animal factors .................................................................................................... 27
Temporal factors ................................................................................................ 34
Spatial factor ...................................................................................................... 36
Spatial influence on animal factors .................................................................... 39
Temporal trend on animal factors ...................................................................... 43
General farm factors .......................................................................................... 48
Comparisons of study data with known references ........................................... 52
Results ....................................................................................................................... 24
Discussion ................................................................................................................. 53
The case definition ............................................................................................. 53
The questionnaire ............................................................................................... 53
The results .......................................................................................................... 54
Temporal factor .................................................................................................. 54
Spatial factors..................................................................................................... 55
Animal factors .................................................................................................... 55
General farm factors .......................................................................................... 60
Plausible cause of spontaneous humeri fracture in dairy cattle ......................... 63
Limitation ........................................................................................................... 64
Conclusion................................................................................................................. 65
References ................................................................................................................. 66
Appendix .......................................................................................................................... 79
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List of table
Table 1-1: Summary of the function of Bone Matrix Protein and the effect of deficiency as
demonstrated in gene deleted mice ............................................................................................ 1
Table 1-2: Summary of the net effect of systemic hormon on the bone dynamics ................. 10
Table 2-1: Derivative variables and its description ................................................................. 26
Table 2-2: Summary statistics for the quality indices of the case animals .............................. 30
Table 2-3: The count of affected front leg by the location (n=69) .......................................... 33
Table 2-4: Count of cases based on the rearing seasons and the location ............................... 36
Table 2-5: The summary statistics of the quality indices of case animals by the region (n=98)
.................................................................................................................................................. 41
Table 2-6: Summary statistics of the walk speed and distance of the case animals within a
month prior to the fracture ....................................................................................................... 49
Table 2-7: The feeding and mineral supplementation profile for the case farms; the proportion
figure stated in the table indicates the number of farms which has been given the listed item
out of 22 case farms. If the figure stated 0.5, 50% of the case farms had given the item to all
animas in the farm according to the age group. ....................................................................... 52
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List of figure
Figure 1-1: A standard load-displacement plot of a solid material. As the load (force)
increase, the material displacement takes place. The unit for load may be in the form of
pressure (Pascal, N/cm2) but displacement can take length (cm. inch) or percentage of
changes ..................................................................................................................................... 11
Figure 2-1: Proportion of missing value on captured variablesError! Bookmark not defined.
Figure 2-2: Proportion of missing value on the derivative variables ...... Error! Bookmark not
Figure 2-3: Trend of the reported cases over 2007-2012 (n=149) .......... Error! Bookmark not
Figure 2-4: The frequency of farm with repeated case season 2007-2012 (n=22) ...........Error!
Bookmark not defined.
Figure 2-5: Case frequency as a function of age and the summary statistics (n=101) .....Error!
Bookmark not defined.
Figure 2-6: Case frequency as a function of cattle breed (n=113) .......... Error! Bookmark not
Figure 2-7: Case frequency as a function of parity (n=115) .... Error! Bookmark not defined.
Figure 2-8: The distribution of breeding worth (BW) and production worth (PW) of the case
animals (n=98) ......................................................................... Error! Bookmark not defined.
Figure 2-9: Scatter plot showing the relationship between breeding worth and production
worth of the case animals (n=98( ............................................. Error! Bookmark not defined.
Figure 2-10: Case frequency as a function of the observed body condition . Error! Bookmark
not defined.
Figure 2-11: Cases frequency as a function of the relative body size to the whole herd (n=98)
.................................................................................................. Error! Bookmark not defined.
Figure 2-12: The proportion of affected leg stratified by the parity (n=69) ............................ 33
Figure 2-13: The proportion of the mode of transporting case animals stratified by the parity
(n=103)..................................................................................... Error! Bookmark not defined.
Figure 2-14: Time series of the spontaneous humeri fracture cases in dairy cattle from 20072012 (n=115)............................................................................ Error! Bookmark not defined.
Figure 2-15: Case frequency based on the absolute month of occurrences (n=105) ........Error!
Bookmark not defined.
Figure 2-16: Case frequency as a function of post-partum period (n=106) .. Error! Bookmark
not defined.
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Figure 2-17: Cases frequency stratified by the prior severe drought experience (n=115)Error!
Bookmark not defined.
Figure 2-18: Cases frequency as a function of the duration between the last month of drought
and the case occurrences (n=88) .............................................. Error! Bookmark not defined.
Figure 2-19: Spatial distribution of the case farms showing the geographical clustering of
case farms into 3 major area: North-North Island, South-North Island and South Island ....... 37
Figure 2-20: The spatial cluster of case farms in North Island ................................................ 37
Figure 2-21: The spatial cluster of case farms in South Island ................................................ 37
Figure 2-22: Case frequency as a function of age stratified by region (n=101) ...............Error!
Bookmark not defined.
Figure 2-23: Case frequency as a function of post-partum period stratified by the region
(n=106)..................................................................................... Error! Bookmark not defined.
Figure 2-24: Case frequency as a function of post drought duration to case stratified by region
(n=88)....................................................................................... Error! Bookmark not defined.
Figure 2-25: Case frequency based on the absolute month of occurrence stratified by region
(n=105)..................................................................................... Error! Bookmark not defined.
Figure 2-26: Proportion of cases in each region stratified by breed (n=113) Error! Bookmark
not defined.
Figure 2-27: Proportion of cases in each region category stratified by parity (N=115) ...Error!
Bookmark not defined.
Figure 2-28: Breeding worth and production worth index of the case stratified by the region
.................................................................................................. Error! Bookmark not defined.
Figure 2-29: Cases proportion as a function of region stratified by the observed body
condition .................................................................................. Error! Bookmark not defined.
Figure 2-30: Proportion of cases by region stratified by the relative body size to the whole
herd (n=98) .............................................................................. Error! Bookmark not defined.
Figure 2-31: Proportion of cases by region stratified by the affected humeri (n=69) ......Error!
Bookmark not defined.
Figure 2-32: Proportion of cases by region stratified by the mode of heifer's transportation
(n=103)..................................................................................... Error! Bookmark not defined.
Figure 2-33: Proportion of cases over observation year stratified by breed . Error! Bookmark
not defined.
Figure 2-34: Proportion of cases over observation year stratified by parity (n=115) .......Error!
Bookmark not defined.
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Figure 2-35: Case frequency as a function of age stratified observation year (n=101) ....Error!
Bookmark not defined.
Figure 2-36: The trend of animal quality indices over five observation years .................Error!
Bookmark not defined.
Figure 2-37 Proportion of cases by observation year stratified by the observed body condition
.................................................................................................. Error! Bookmark not defined.
Figure 2-38: Proportion of cases by observation year stratified by the relative body size to the
whole herd (n=98) .................................................................... Error! Bookmark not defined.
Figure 2-39: Proportion of cases by observation year stratified by the affected humeri (n=69)
.................................................................................................. Error! Bookmark not defined.
Figure 2-40: Proportion of cases by observation year stratified by the mode of heifer's
transportation (n=103) ............................................................. Error! Bookmark not defined.
Figure 2-41: Case frequency as a function of the average daily walk distance in a month prior
to the fracture (n=95) ............................................................... Error! Bookmark not defined.
Figure 2-42: Case frequency as a function of the average daily walking speed within a month
before fracture (n=90) .............................................................. Error! Bookmark not defined.
Figure 2-43: Nutrient supplement of different group in the case farms (n=22)....................... 50
Figure 2-44 Basal diet of different age group in the case farms (n=22) . Error! Bookmark not
Figure 2-45: Comparison between case animals’ quality indices with the national reference
2011 produced by Dairy NZ .................................................... Error! Bookmark not defined.
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Chapter 1
A general introduction to the bone biology and literature review
1.1 Introduction
Bone is the hardest specialised connective tissue of the vertebrates which contributes
between 15-22% of total body weight of ruminants depending on the age group; the lower
age group consistently shows the higher bone to weight percentage (Martinsson & Olsson,
1993; Piedrafita et al., 2003; Refsgaard Andersen, 1975). The bone strength is chiefly
contributed by the mineral salt that constitutes 45% of adult mammals’ wet bone weight,
which predominantly calcium (37%) and phosphorus (18.5%) (Carter & Spengler, 1978).
Based on the strength per unit weight, bone (femur) is apparently stronger than aluminium
alloy (Fung, 1993; Kaplan, Lee, & Keaveny, 1994) hence spontaneous fracture on a healthy
bone is next to impossible. While bones appear to be rigid, it is inherently dynamic and
endures active process of model and remodel throughout life (Delahay 2010) as a response to
physiological need, trauma, disease, use or disuse (McGeady, 2006), which differentiate
bones from any inert hard materials such as aluminium alloy.
This general introduction will give an overview of bone biology and describe the
potential differential diagnosis of spontaneous/low force fracture that serves as a guide in
investigating the potential aetiology of the spontaneous humeri fracture. The literature cited
may come from different species besides dairy cattle, especially in introducing the bone
1.2 Bone composition
As any other connective tissues, bone tissue that is originated from the embryonic
mesoderm, contains cells, fibre and amorphous ground substance(McGeady, 2006). The
cellular components of bone that actively involved in model and remodeling process are
osteoblast, osteocytes and osteoclast(Jee, 1989). The fibrous component of bone tissue is
primarily type one collagen. The amorphous substances of the bone are mainly organic
materials that excreted by the cellular component: sulphated glycosaminoglycan and
glycoprotein; as well as inorganic materials that contribute to the tensile strength known as
calcium-phosphate-carbonate complex (Gentili & Cancedda, 2009).
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Bone cells
The osteoblasts are responsible for the construction of the bone tissue. Osteoblasts
derived from the lineage-restricted potential cells in the mesenchyme that are able to
differentiate into either fat cells or osteoblasts (McGeady, 2006). The presence of Cbfa1
promotes the osteoblasts' formation (Karsenty, 2000). Histologically, osteoblasts are cuboidal
and columnar in shape with large, round, centrally located nuclei and could be found on the
bone lining(Jee, 1989). The osteoblasts have receptors for systemic hormones such as
oestrogen and PTH (Ernst, Parker, & Rodan, 1991; Ono et al., 2007)indicating that the
endocrine system may dictates the osteoblast activities; and secrete other local regulators that
could influence other cellular processes such as activation (via RANK-Ligand) or
neutralisation (via OPG) of osteoclastogenesis (F. Gori et al., 2000). The activated osteoblasts
synthesize organic matrix (osteoid), which will be calcified and entrapped the cells in it. In
the matrix, osteoblasts differentiate into the osteocytes. The remaining osteoblasts on the
bone lining are either differentiates and becoming the lining cells that serve as a protective
cover of the new bone or undergo apoptosis and disintegrate (Xing & Boyce, 2005).
The osteocytes are the entrapped, mature osteoblasts that become less active in the
secretions of the organic matrix (McGeady, 2006). The site where osteocytes are located is
referred to lacuna. As the osteocytes embedded deeper into the mineralised matrix, the
cytoplasmic content becomes less but the cytoplasmic processes that lie within the calcified
matrix establish contact with other osteoclasts (Eurell & Van Sickle, 1998). The cytoplasmic
canals, known as the canaliculi plays an important role in low molecular weight substance
transfer between osteoclasts and the stimulation of the cell linings or the osteoblast precursor
for a targeted remodelling process (Bonewald, 2007).
The osteoclasts are the bone cells that responsible for bone matrix resorption. The
osteoclasts act to dissolve the inorganic component of the bone matrix under through the
reduction of environment pH and the degradation of organic component via the proteolytic
enzymes (McGeady, 2006). The attachment site of the osteocytes to the bone in which active
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bone resorption occurs is called ruffle borders. The matrix-resorption activities produce
erosion lacuna that remains even after the cells are no longer present. Histologically, the
active osteoclasts are large (up to 150um in diameter), multinucleated (up to 50 nuclei),
acidophilic cytoplasm and located at the surface of the surface of bone (Eurell & Van Sickle,
1998; Nicolin et al., 2006). Osteoclasts derived from the linage-restricted pluripotential cells
that also produce macrophages and monocytes, which are circulating in the blood and bone
marrow (Eurell & Van Sickle, 1998). The osteoclast precursors that are activated by the
osteoblastic RANK-L merge to become multinucleated, large cells. While resorping the bone
matrix, BMPs will be released, which regulates the osteoclastic activities (Dieudonné, Foo,
Van Zoelen, & Burger, 1991). When the bone resorption is over, the osteoclasts undergo
apoptosis and disintegrate (Xing & Boyce, 2005).
Bone matrix
The bone matrix is consisting of the other two components (beside cells) that
classified bone as a type of connective tissue: fibre and amorphous compounds (McGeady,
2006). The fibres that are produced by osteoblasts are mainly the collagen type-I that exist in
triple helices form. The collagen provides strength to the bone by their spiral orientation in
the osteon lamella and the right angle alternation to the adjacent lamella (Eurell & Van
Sickle, 1998). The inorganic substances of the amorphous compound of the bone matrix are
chiefly calcium and phosphate. The minerals are deposited within the collagen fibre network
in the form of crystal thus further augment the tensile strength of the bone. The inorganic
substance is accounted for approximately 60% of the dry bone weight (Carter & Spengler,
1978). The bone matrix also contains several proteins that possess important bone
homeostasis function. The expression of the matrix protein is controlled and coordinated by
the encoding genes through complex mechanisms that are directly or indirectly modulated by
systemic hormones (Zaidi, 2007). The function of the matrix proteins may overlap, but
certain matrix proteins have specific deficiency effect on bone. The function and regulation
of the bone matrix have been reviewed elaborately by Gunberg (2003) and Young (2003),
and the summary of bone matrix function is shown in table 1-1.
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Table 1-1: Summary of the function of Bone Matrix Protein and the effect of deficiency as demonstrated in gene
deleted mice
Functions in bone
Collagen fibril
Regulate TGF-β
Binds to integrin
receptors; proliferation
and differentiation of
Initiate mineralization
of collagen ; matrix
Osteopontin (OPN)
Promotes osteoclast
attachment to
mineralised surface;
Bone primary
Matrix extracellular
Inhibitory role in bone
protein (MEPE)
formation and
involved in renal
phosphate regulation
Regulation of bone
Vit K dependent Osteocalcin (OCN)
Regulation of bone
mineralisation –
promote mineralisation
References: (Gundberg, 2003; Young, 2003)
Effect of deficiency
(Knock-out gene in mice)
Reduction in osteoblast precursor and less
responsive to TGF-β hence causing a lower
peak bone mass
Amplify the effect of biglycan deficiency
Death at the early stage
Osteopenia in older animals
Resistant to PTH, reduced mechanical
stress- induced bone resorbtion; increase in
trabecular bone volume
Higher trabecular bone volume, associated
with lower bone remodelling
Increased bone formation and bone mass
Increase in functional and quality of bone
Disproportionate mineralisation of cartilage
and arteries
1.3 Bone function
With the variation in the shape, density, tensile strength and location, bone serves many
important functions including support, protection, movement, blood cells' production, mineral
storage (Clarke, 2008; Eurell & Van Sickle, 1998; Jee, 1989; McGeady, 2006).
Support function
The common function of any connective tissue is to provide cohesion and internal
support. The bone assists the function of other soft tissues by providing attachment sites.
Ligaments, muscle and tendons are the examples of tissue that benefits directly the generic
function of bone. The bone also supports another function such as hearing through the ability
to vibrate as a response to audio stimuli (Monsell, 2004); reproduction in dogs (Kent & Carr,
2001)-the presence of Os penis enables coitus to happen.
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Protection function
The bone provides significant protective properties on many vital organs via its shape
and tensile strength (Clarke, 2008; Kent & Carr, 2001). The body systems that enjoy the
protective properties of bones;
The central nervous system enjoys an extensive protection by the bones by the skull
and vertebrae that act as a tough case which provides shelters that withstand the
external force.
The circulatory and respiratory system in the thoracic cavity is protected by rib cage
and sternum.
Visual system receives a substantial protection by the virtue of ocular sockets.
Movement function
Animal movement is made possible by the synchronised contraction and relaxation of
muscles, which attached to the bone. Bones act as levers that assist the body movement on
different planes. The type of movement is related to the structure in which two bones are
attached. The socket and ball attachment (hip and shoulder) allows all planes movements;
hinge on attachment (elbow) allows one plane movement; gliding attachment (vertebrae)
allows the flat surface of one slip over the other (MacConaill, 1948; Vogler & Bojsen-Moller,
Blood cells production function
Blood cells' production (hematopoiesis), prenatally, take place happens in many
organs such as liver, spleen, lymph node and bone marrow (Tavian & Peault, 2005). After
birth, the production is taken over mainly by bone marrow and partly by lymph node.
Nevertheless, maturation or activation of many blood cells produced by bone marrow
happens in the other organs. The production began with the differentiation of hematopoietic
stem cell under the influence of many sets of cytokines (Taichman, 2005) to produce
different cell progenitor that will give rise to specific blood cells (Pittenger et al., 1999).
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Mineral storage function
The bone is accounted for 15-22% of body weight (Piedrafita et al., 2003).
Approximately, 45% of wet bone weight is mineral salts; of which 37% is calcium (Carter &
Spengler, 1978). Hence, via a simple calculation, a 350kg cow may have roughly 19kg of
calcium, which is stored in the bone. The above example illustrates the storage capacity of
bones. When it is necessary, the mineral reserve in the bone can be used to maintain the
narrow range of plasma calcium of 8-10mg/dl (Goff, Reinhardt, & Horst, 1991). The
conditions which normally necessitate the withdrawal of bone mineral reserve are pregnancy
and lactation (Braithwaite, 1983; Oliveri, Parisi, Zeni, & Mautalen, 2004). When the mineral
deficiency has been lifted, the mineral deposition takes place again to the optimal level. If the
bone mineral withdrawal was prolonged, for example, in extended lactation, the bone density
could be significantly reduced (Sowers M & et al., 1993). The bone’s strength, at the same
time could be compromised as the mineral crystal function is to strengthen the bone structure
(Carter & Spengler, 1978).
1.4 Long bone growth
The long bone growth starts in the embryonic stage. The mesodermic layer that
aggregates under the influence of BMP, differentiate into perichondrium and become the
template of future bone (McGeady, 2006; Sykaras & Opperman, 2003). The interstitial
growth at the both end in the perichondrium is regulated by PTHrp and Indian Hedge Hog
(ihh). PTHrp stimulates the proliferation of chondroblast, which elongates the cartilaginous
template while ihh stimulates the differentiation of chondroblast into chondrocytes, which
increases the width (Karp et al., 2000; McGeady, 2006). TGF-β, however, regulates the
hypertrophy of the chondrocyte; therefore, indirectly regulates ihh secretion by the
chondrocyte (Vortkamp et al., 1996). The chondrocytes excrete substance such as amorphous
ground substance, collagen and fibronectin to fill in the matrix. Alkaline phosphatase that
secreted by the hypertropic chondroblasts promotes mineral deposition of the matrix hence
trapped the chondrocytes in it (Orimo, 2010). As the chondrocytes entrapped in the calcified
matrix degenerates and disintegrates, the primitive medullary space is formed in the
diaphysis. The medullary space will be invaded by the periosteal bud form the developing
periosteum that consists of blood vessels and mesenchymal cells; that later differentiates into
pre-osteoblast and pre-osteoclast (McGeady, 2006). The invasion of the periosteal bud
initiates the remodelling of the calcified chondrocytes matrix, which is known as the primary
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centre of ossification. The secondary centres of ossification occur in the similar manner of the
primary ossification, but it occurs at the end of the long bone template (epiphysis) (Eurell &
Van Sickle, 1998).
The growth in the long bones is performed by the cartilaginous layer that remains after
the invasion of the primary and secondary periosteal bud. The cartilaginous layer, which is
known as physes, grows inwards into the diaphyseal region owing to the columnar
arrangement of the chondrocytes(McGeady, 2006). The reserve zone of the growth plate,
which differentiates into chondroblast, move towards the diaphysis to enter the phases of
proliferation, hypertrophy, resorption and ossification (Eurell & Van Sickle, 1998). The rates
of chondrocytes' productions in every column are highly regulated by the local hormones; ihh
controls the production of PTHrp, and PTHrp promotes the chondroblast differentiation. The
local hormones' regulation is important to ensure the simultaneous growth of the growth
plate; hence uniform elongation of long bone can be seen (Karp et al., 2000; McGeady,
The process of width and circumference growth of long bones is the effect of a highly
regulated, different rate of osteoblast and osteoclast activities in remodelling the ossified
bone matrix (Burr, 2002). The endosteal resorption lags behind the periosteal expansions
hence the bone gains the width but maintains the shape (Eurell & Van Sickle, 1998). If the
osteoclast fails to resorb the bone, the bone becomes dense from the mineralisation of the
cartilage (Van Slyke & Marks, 1987).
1.5 Growth in flat bones
The flat bones such as skull, mandible and clavicle do not undergo the same elongation
process as in long bones (McGeady, 2006). This is because of the absence of cartilage stage
in the flat bones (Eurell & Van Sickle, 1998). The fibroblast within the well-vascularized
connective tissue that entrapped the future flat bones differentiates into osteoblast, produce
the osteoid matrix which subsequently calcified to form bone spicules. This isolated bone
development within connective tissue is known as the centre of ossification, which intensifies
and radiates into several directions to form cancellous bone. Later, the osteoclasts resorb the
cancellous bone and replaced by lamellar bone. The outer mesenchyme also differentiates
into the periosteum that fuses with both sides of the developing cancellous layer to produce
bone plates. The expansion of the centre of ossification is responsible in increasing the
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thickness of the flat bone (Eurell & Van Sickle, 1998; McGeady, 2006; B.R Olsen, 1999; B.
R. Olsen, Reginato, & Wang, 2000; Yang, 2009).
1.6 Bone remodelling
During the inert situation, sclerostin is secreted by osteocytes (Poole et al., 2005); travel
through canaliculi to the bone marrow, and inhibits Wnt pathways that would produce the
cellular expression which stimulates bone formation (Li et al., 2005). In situation that leads to
the death of osteocytes, two major events will take place:
1. Sclerostin that normally be secreted will be reduced hence the Wnt pathways for cell
expression on certain bony location will resume (Li et al., 2005; Poole et al., 2005).
2. The adjacent osteoclasts secrete other factors such as prostaglandin, nitric oxide and
growth factors that assist in the remodelling process (Bakker, Soejima, Klein-Nulend,
& Burger, 2001).
The adjacent stromal cells that are free from the influence of sclerostin generate preosteoblasts and secrete M-CSF that assists in preosteoclastic generation; while the lining cells
merge with the nearby blood vessels and allowing pre-osteoclastic cells to flood the bony
area to be remodelled (Matsuo & Irie, 2008). The pre-osteoblasts proliferate and secrete
cytokines while expressing the surface RANK-L which activates the preosteoclast to merge
and form the multinucleated osteoclasts (Matsuo & Irie, 2008). The osteoclasts bind and
digest the bone matrix using the H ion and Cathepsin-K until receiving signals to cease the
activity by the bone growth factor: BMPs, IGF and TGF-B (Dieudonné et al., 1991; Fuller et
al., 2008). The osteoclasts then undergo apoptosis under the influence of oestrogen and other
factors as to allow for bone formation by osteoblasts (Kameda et al., 1997). The preosteoblasts, under the influence of systemic (estrogen, PTH) and local hormones (IL-1, IL-6)
proliferate and differentiate into osteoblasts (Neve, Corrado, & Cantatore, 2011). The
osteoblasts stop expressing surface RANK-L and secreting OPG that collectively stops the
activation of pre-osteoclasts by the pre-osteoblasts (Kobayashi, Udagawa, & Takahashi,
2009). The mature osteoblasts lined-up the resorption cavity and produce osteoid. Some
osteoblasts trapped in the osteoid and while the rest will continue to produce the bone matrix;
some differentiate into osteoblasts in the bone matrix, or become flat cells that line the bone
(Hill, 1998). The new, mature osteocytes re-establish the link between the bone and the
surface cells and continue transmitting sclerostin to surface cells that suppress the cellular
expression by the Wnt pathway (Poole et al., 2005).
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1.7 Bone regulators
Local regulators
Besides the regular endocrine hormones that modulate the bone dynamics, bone cells
also produce local bone regulators, which act on the nearby cells; influencing the
proliferation, differentiation, or survival (Hill, 1998). The production of the local regulators
such as sclerostin by osteocytes in preserving the quiescence of bone environment may be
independent of endocrinal hormones (Poole et al., 2005) but many other local regulators such
as IGFs are produced in the presence of PTH (Lombardi et al., 2010).
Growth factors
Growth factors are polypeptide that is synthesized by specific tissue, which act by
binding to the specific trans-membrane receptors of the target cells and activate the
transcription-translation mechanism to produce proteins for intra cellular usage or exported
(Trippel, Coutts, Einhorn, Mundy, & Rosenfeld, 1996). The general function of the growth
factors as demonstrated in the cell culture experimental studies are influencing proliferation,
differentiation and protein synthesis in osteoblastic cultures as well as bone formation in
animal models (Bolander, 1992; Boyne, 1996; A. Yamaguchi et al., 1996). There are several
families of growth factors identified: bone morphogenetic proteins (BMPs), transforming
growth factor beta (TGF-β), insulin-like growth factors I and II (IGF-I and IGF-II), platelet
derived growth factors (PDGF) and fibroblast growth factors (FGF); however, only BMPs are
known to provoke heterotopical bone formation by osteoinduction of the undifferentiated
mesenchymal cells.(Solheim, 1998). The BMPs is important in the regulation of bone
induction, maintenance and repair (Sykaras & Opperman, 2003). A simple example that
could explain the importance of BMP is the fate of preosteoblast; without the presence of
BMP, Cbfa-1 that activates the gene transcription in the stem cells to differentiate into
osteoblast may not be produced, hence the stem cells would turn into adipose cells (Akira
Yamaguchi, Komori, & Suda, 2000). Most of these growth factors are stored in the bone
matrix (Bonewald & Mundy, 1990); therefore, bone resorption by osteoclast may release the
growth factors and activates the osteocytes' lineage proliferation and differentiation, which
promote bone formation.
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Cytokines are soluble signaling proteins that produced by haematological cells, which
could act as a local regulator of bone cell metabolism (Goldring & Goldring, 1990).
Osteoblasts produce a few cytokines: macrophage colony stimulating factor (M-CSF),
granulocyte-macrophage colony stimulating factors (GM-CSF), interleukin-6 (IL6) and
tumor necrosis factors (TNF-α), which serve as paracrine regulators of osteoclasts as well as
autocrine regulators for osteoblast (Metcalf, 1989). The cytokines' production is highly
regulated by other regulators such as PTH (Feyen, di Padova, Trechsel, & Elford, 1989) and
oestrogen (Masiukiewicz, Mitnick, Grey, & Insogna, 2000). Although the specific function of
each cytokine may include the both bone formation and resoption, the main function of
cytokines is more related to the latter. IL-6 that influence osteoblast to express RANKL and
M-CSF that important in the maturation of osteoclast are the key element for
osteoclastogenesis that leads to bone resorption. (Teitelbaum, 2000)
Systemic regulators
Hormones are organic chemicals that are made by a group of specialised tissues that
act as a messenger for other parts of tissue with the specific receptor for the hormone to act.
Hormones that are excreted directly into the blood stream for the transportation to the target
tissue are called the endocrine hormones, whereas the group of hormones that are secreted
through a duct before they reach the target tissue with or without the medium of blood as the
transporter is called the exocrine hormones (Griffin & Ojeda, 2004). The process of getting
the hormones to produce the intended effect may not be direct. Briefly, in order to have the
growth of the long bones under the influence of thyroid hormones, thyrotropin-releasing
hormone has to be produced by the hypothalamus to stimulate the anterior pituitary to
produce TSH. The TSH will stimulate the thyroid gland to produce thyroid hormones that
will act on the specific receptors in the bone tissue to produce the desired effect (Duncan
Bassett & Williams, 2003). When the intended effect has been fulfilled, a negative feedback
will be produced to signal the tissue to stop producing the hormones (Scanlon & Toft, 2000).
The following paragraph illustrates on how the systemic hormone inter-related to each
other in maintaining calcium homeostasis, which affects the bone dynamic. The example
given here is relating the dependency on PTH for vitamin D activation and the antagonism
between PTH and calcitonin on maintaining the narrow calcium plasma range.
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Parathyroid hormone
Parathyroid Hormone (PTH) is a peptide hormone produced the chief cells of the
parathyroid gland. PTH is responsible in increasing the blood calcium level by acting upon
the PTH-receptor in the bone and kidney. In the bone tissue, PTH reduces sclerostin (Bellido
et al., 2005), and OPG but increases the expression of RANKL (Huang et al., 2004) which
collectively promotes bone resorption. In kidneys, PTH acts to increase the blood calcium
level by increasing the calcium reabsorption that primarily occurs in the distal tubules
(Kennedy, Flanagan, Mills, & Friedman, 1989) and enhancing the phosphorus excretion
(Clark, 1991) thus the calcium-phosphorus blood ratio can be increased. Concurrently, PTH
involves with the modulation of 25-hydroxy vitamin D activation into 1, 25-dihydroxy
vitamin D (Brenza et al., 1998). The activated vitamin D is required to activate calbindin
(Hemmingsen, 2000)to intensify the intestinal calcium absorption. The secretion of PTH is
highly regulated by the calcium level in the blood; a low blood calcium level will trigger the
secretion while a high blood calcium level will serve as a negative feedback to the
parathyroid gland (Loupy et al., 2012). Unfortunately, a low blood magnesium level may also
compromise the regulation mechanism of the PTH secretion (Rude, Oldham, Sharp, &
Singer, 1978). In normal circumstances, magnesium modulates the calcium release from the
sarcoplasmic reticulum (Meissner, Darling, & Eveleth, 1986)of the calcium-sensing receptors
hence the PTH regulation is triggered primarily by the influx of the extracellular calcium
(Kantham et al., 2009). In other words, the state of hypomagnesemia could create a false
signal of plasma calcium sufficiency, which incapacitates the PTH secretion which could lead
to the state of hypocalcemia.
Calcitonin is a peptide hormone produced within the parafollicular cells of the thyroid
gland when there is an increase above the normal plasma calcium level (Griffin & Ojeda,
2004). It works antagonistic to PTH by temporarily decreasing the blood calcium level upon
stimulating the calcitonin-receptor in the bone, kidney and intestine. Calcitonin receptors that
are found abundant in the osteoclast suggesting calcitonin preserve the bone by inhibiting
osteoclast activities (Samura, Wada, Suda, Iitaka, & Katayama, 2000). The osteoclasts'
inhibition mechanism by calcitonin is important in skeleton preserving effort, especially
during the physiologically increased in calcium demand such as pregnancy and lactation
(Kovacs & Kronenberg, 1997). In kidney, calcitonin inhibits the tubular calcium reabsorption
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(de Rouffignac & Elalouf, 1983), while the role of calcitonin on the intestinal calcium
absorption is uncertain as the result from experimental studies on animals was not unanimous
(Jaeger, Jones, Clemens, & Hayslett, 1986; Matsui, Kuramitsu, Yano, & Kawashima, 1983).
Calcitonin production can also be stimulated by other stimulants beside the blood calcium
level such as chronic elevation of gastrin (Erdogan, Gursoy, & Kulaksizoglu, 2006). Together
with PTH, calcitonin is important in maintaining the calcium-phosphorus homeostasis.
Vitamin D
Vitamin D is a special lipid hormone that can be synthesized from the cholesterol in
the skin by the UVB (290-310 nm wavelength) (Slominski & Wortsman, 2000). The product
of the photosynthesis: a pre-vitamin D (7-dehydrocholesterol) (Tian & Holick, 1999), has to
be activated before functioning as a regulator of bone density. The pre-vitamin D can be
converted into 25-hydroxy vitamin D (calcidiol) in the liver. In the presence of PTH, calcidiol
can undergo hydroxylation to form 1, 25-dihydroxy vitamin D (calcitriol) in kidneys (Holick,
1994). This active form vitamin D binds to the vitamin D receptors which are located in the
kidney and intestine to regulate the expression of transport protein such as TRVP6 and
calbindin. The TRVP6 act as channels that allow selective uptake of calcium ion into the
intestinal epithelium (den Dekker, Hoenderop, Nilius, & Bindels, 2003). While the calcium
ions are in the enterocyte, Calbindin binds to the ion and facilitates the movement across the
enterocytes (Bolt, Cao, Kong, Sitrin, & Li, 2005). The presence of calbindin in bone and
cartilage suggest that vitamin D may involve in bone tissue mineralisation (Balmain, 1991).
There are many other systemic hormones that may influence the dynamicity of the bone.
Table 1-2 summarises the net effect of selected systemic hormones on the bone density.
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Table 1-2: Summary of the net effect of systemic hormon on the bone dynamics
Increase Bone
(Jilka et al., 1999; Lindsay et al.,
1997; Mcsheehy & Chambers,
(Ernesto Canalis & Delany, 2002;
Gronowicz, McCarthy, & Raisz,
1990; Lukert & Raisz, 1990)
(Allain, Chambers, Flanagan, &
McGregor, 1992; Mundy,
Shapiro, Bandelin, Canalis, &
Raisz, 1976; Uzzan et al., 1996)
Increase Bone
Vitamin D
Gonadal steroids
(Andreassen, Jørgensen, Oxlund,
Flyvbjerg, & Ørskov, 1995;
Menagh et al., 2010; Ohlsson,
Bengtsson, Isaksson, Andreassen,
& Slootweg, 1998)
(Baldock et al., 2006; Bordier et
al., 1978; Erben, Scutt, Miao,
Kollenkirchen, & Haberey, 1997)
(Chow, Tobias, Colston, &
Chambers, 1992; Sjögren et al.,
2009; Yilmaz et al., 2005)
Decrease Bone
Gonadal steroids
Decrease Bone
(Ongphiphadhanakul, Piaseu,
Chailurkit, & Rajatanavin, 1998;
Samura et al., 2000; van der Wiel
et al., 1993)
(Chiang et al., 2009; Francesca
Gori, Hofbauer, Conover, &
Khosla, 1999; Vanderschueren et
al., 2004)
(Kim et al., 2007; Kim et al.,
2006; Rauch et al., 2010)
1.8 Biomechanics of bone
Any solid materials inherently have the properties of stiffness and toughness. The
stiffness of a solid material, which normally estimated using Young’s modulus of elasticity
using pascal (Pa) as the measurement unit, is a measure of the force over a reversible
displacement (Riley & Zachary, 1989). A stiff material requires a high amount of force to
produce a unit of reversible strain. Currey (1999) stated that a solid material can be
categorised as stiff if it had a Young’s modulus value higher than 5GPa. A quick example to
comparatively illustrate the stiffness properties of solid materials using Young’s modulus
value: the reinforced thermoplastic natural rubber (0.34GPa)(Sahrim, Mou'ad, Yahya, &
Rozaidi, 2011), bovine cortical femur bone (14GPa) (J. D. Currey, 1979)and diamond
(1050GPa) (Savvides & Bell, 1993).
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Elastic region
Figure 1-1: A standard load-displacement plot of a solid material. As the load (force) increase, the material
displacement takes place. The unit for load may be in the form of pressure (Pascal, N/cm2) but displacement can take
length (cm. inch) or percentage of changes
The maximum force on which a material could return to the original shape upon the
removal of force correspond to the yield point (Riley & Zachary, 1989). On the loaddisplacement plot (Fig 1-1), the yield point represents the gradual transition between the
linear and the non-linear curve. Any forces placed on a solid material, which exceeded the
yield point may permanently misshape the solid material even after the force is removed.
When a solid material breaks, it indicates that the ultimate strength of the material was
The displacement value that corresponded with the yield point divides the stress-strain
plot into two; the lower displacement region that covers the linear plot of the loaddisplacement curve is called the elastic region, and the higher displacement region that covers
the non-linear curve of is called the plastic region. The size of the elastic region can be used
to compare the stiffness of two materials. The smaller the elastic region means the lesser
work is needed to misshape the material. The size of the plastic region indicates the
brittleness of the material. The smaller the plastic region means the lesser work of force is
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needed to break the materials after the yield point has been reached. Both areas, the elastic
and plastic region, indicate the toughness property of a solid material.
The bone tissue is a unique lightweight composite material, which exhibits excellent
strength and stiffness to provide structural support (McNamara, 2011) . The mineral and
collagen content of bones which contributes to rigidity and flexibility, strongly affect the
mechanical properties of bone(Follet, Boivin, Rumelhart, & Meunier, 2004). The
composition varies depending on the function of the bone (J. D. Currey, 1979). Tympanic
bulla (earbone), which function is to convert the audio wave into the audio signal through
vibration, has the mineral content of 86% and Young’s modulus of 31.3GPa, while the femur
bone, which function is to support weight, has 67% mineral content and Young’s modulus of
13.5GPa (J.D. Currey, 1999).
On the age factor, based on Brear (1990), three months old polar bear had a lower
femoral bone mineral content (235 mg calcium/g bone) than of a three years-old polar bear
(259 mg calcium/g bone). The Young’s modulus of the three years-old polar bear was three
times higher than the three months-old polar bear. This shows that the young can withstand a
large bone displacement better than the old, owing to the lower bone mineral content, which
leads to the phenomena of green stick fracture in the young: bone undergoes a large
displacement without break. As the elasticity decreasing with age, the strength of the bone
increases with the increase of bone mineral content. The advancement of age from three
months to three years had the calcium content per gram femur bone of the polar bear increase
by 10%; the yield strength increases by 70% (Brear, Currey, & Pond, 1990) to meet the
increasing demand in its structural functionality. As the animal grows bigger, the weight
needed to be supported efficiently. The increasing demand in tensile strength, especially on
the limb’s bone is met by increasing the mineral content and cortical diameter of the
diaphysis (Follet et al., 2004; C. H. Turner, 2006).
The strength of a long bone is not uniform. As for an example, adult human femur has
longitudinal compressive strength of 205MPa and a longitudinal tensile strength of 135MPa
(Joon, 1999). That means femur bone is easier to break when the femur is pulled that pushed
longitudinally. Conversely, human femur has the shear strength of 52MPa (C. H. Turner,
Wang, & Burr, 2001), which means pulling and rotating the bone half the forces needed to
pull-breaking the shaft would cause the bone to break. A spiral or oblique fracture of long
bone is an indication that shear stress involved in the fracture (C. H. Turner et al., 2001).
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1.9 Low force fracture
Bone fracture is also known as the break of bone continuity (McGuigan, 2010). It
happened when the loading force exceeded the ultimate strength of the bone causing
irreversible permanent damage (Einhorn, 1992). Excessive force is needed to fracture a
normal healthy bone due to the presence of mineral and collagen in the bone that strengthen
the structure. Conversely, an excessive mineralisation of bone as in osteopetrosis does not
contribute to the ultimate bone strength (Stark & Savarirayan, 2009). A standard has been
proposed that any deviation from the normal bone mineral density exceed 2 the standard
deviation of the normal mean BMD of young healthy population, would put the bone on a
risk of fracture (Genant et al., 1999).
Low force or spontaneous fracture is a common term to describe the incident of bone
fracture without obvious involvement of excessive external force (Dolinak, 2008; Horiuchi et
al., 1988). The spontaneous fracture happened because the inherent strength to withstand
fracture failure has been reduced tremendously that normal daily force load exceeded the
ultimate strength of bone. Based on the underlying cause of the spontaneous fracture, the
fracture can be categorised as pathologic (Torbert & Lackman, 2010) or fatigue(J. M. Morris,
1968). The importance of identifying the underlying causative agent of low force fracture is
that the intended treatment options and post –treatment care may not be the same (Hallel,
Amit, & Segal, 1976; Torbert & Lackman, 2010).
The following paragraph is to illustrate some of the common conditions that would that
would lead to the reduction of bone ultimate strength and posed an increased risk of low force
Osteoporosis is a major health threat to the aging human population worldwide on
which a global strategy was indicated by WHO to prevent and control the osteoporosisrelated complications (Genant et al., 1999). The WHO task force on osteoporosis predicted
that the worldwide incident of hip fracture due to osteoporosis that was recorded 1.7 million
in 1990 could increase to more than 6 million in 2050 (Genant et al., 1999). Osteoporosis is
generally known as the reduction of bone mass and micro-architectural deterioration of bone
tissue, which increases the bone fragility (Rosenzweig & Pignolo, 2010). As bone is a
dynamic tissue which undergoes constant remodeling, change in bone density is a relative
statement. Therefore, WHO has specifically defined osteoporosis as the reduction of BMD >
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2 standard deviation of the BMD of healthy young age group (World Health Organisaton,
1994). During the embryonic stage, the bone started to increase the mineral content and
density from the second to third trimester (McGeady, 2006). Approximately, 35 grams of
calcium are needed to support human embryonic bone development (Kovacs & Kronenberg,
1997). After birth, bones continue to increase the mineral content but the bone density may
not increase as fast due to the rapid elongation of the axial and appendicular bones. The
optimum bone density reaches the optimum level only after the puberty and remains within
the same range until 50 (female) and 65 (male) for healthy normal human being (Bachrach,
2001). Reduction in bone mass is a result of imbalance in the activities of osteoclast and
osteoblast. Obviously, the osteoclast outperformed osteoblast. Reduction of bone mass in
osteoporosis is a subclinical condition until the specific function of bone is affected. Human
case of osteoporosis is usually presented with tenderness, recurring back and neck pain,
which detected at the advance stage of osteoporosis (Glaser & Kaplan, 1997; Orwoll & Klein,
1995). There are many risk factors claimed to cause such imbalance, including aging,
physical stress, nutritional deficiency, hormonal and genetic disorder, as well as the lifestyle
(Genant et al., 1999).
Osteoporosis can be grouped into two major categories depending on the underlying
cause: Primary and secondary osteoporosis.
Primary osteoporosis
Primary osteoporosis is a bone disorder of unknown origin or as a result of aging
(Glaser & Kaplan, 1997). The peak bone mass is reached within a few years after the closure
of the long bone epiphyses, and the BMD remains within its normal range until the sex
hormones declined significantly (Bachrach, 2001). Primary osteoporosis is associated with
the gradual declination of sex hormone (Riggs, Jowsey, Kelly, Jones, & Maher, 1969). The
reduction in bone density is accelerated when the sex hormone producing organ is surgically
removed (Russell T. Turner, Wakley, & Hannon, 1990) or the permanent natural cessation of
the primary function occurred as in the post menopause period (R. T. Turner, Riggs, &
Spelsberg, 1994).
In female, oestrogen is produced primarily by the ovaries but other tissues such as
liver and adrenal gland and adipose has the capability of producing estrogen in a smaller
quantity through the aromatisation of C19 steroids (Simpson, 2002). During pregnancy, the
placenta becomes the primary estrogen producing tissue (Koh et al., 2012). There are three
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types of estrogen depending on the presence of the hydroxyl group on the carbon ring:
Estrone (E1), estradiol (E2) and estriol (E3). E2 is the most potent form of estrogen is mainly
produced by the gonads and the major estrogen group during the active reproductive years
(Longcope, 1998).
Estrogen is readily diffused across cell membrane and attach with the intercellular
estrogen receptors (ER) to control gene expression. Many bone cells except osteoclast and
chondrocytes are rich with ER hence estrogen has a direct influence on those cells
(Vanderschueren et al., 2004). Estrogen was found to be beneficial in preserving the bone due
to its ability to reduce the prevalence of mature osteoblast apoptosis (Almeida et al., 2010).
Some researchers have linked estrogen to the suppression of inflammatory cytokines that
stimulate osteoclastogenesis and bone resorption, such as IL-1, TNF-α, and IL-6 (Most et al.,
1995; Sunyer, Lewis, Collin-Osdoby, & Osdoby, 1999); while other suggest that oestrogen
induces Fas-ligand in osteoblasts to regulate the differentiation of preosteoclast (Krum et al.,
2008). On the other hand, the failure of the Wnt/β-catenin pathway to adjust the bone cell
response to the mechanical strains has been suggested in estrogen deficient individual, which
leads to the inability to maintain the appropriate bone mass. (Armstrong et al., 2007).
The androgens, which are the main hormone that induced fetal sexual differentiation
and the expression of male characteristic at the puberty, are not only produced by Leydig
cells in the testicle but also produced in a small quantity in the non-gender specific tissue
such as adrenal glands. Hence androgens are present in female serum as the estrogens are
present in male serum. Labrie et al (1997) reported that in serums of human adult between the
age of 20-30 years, mean serum testosterone level in female is 7% of the serum testosterone
level in male while the estradiol in male is 36% as high as in female. The presence of genderspecific hormones in the opposite sex is due to the capacity of the androgenic steroid,
androstenedione, to undergo hydroxylation into testosterone or aromatisation into estrogen
(Riggs, Khosla, & Melton, 2002). Androgen can bind to androgen receptors (ARs) which
present in nearly all bone cells while androgen-derived oestrogens bind to the ERs. The effect
of both estrogen and androgen in preserving the bone may overlap but the distinction of bone
responses to the stimulation of ARs and ERs in gene knock-out mice has been reviewed by
Vanderschueren et al (2003).
In relating the primary osteoporosis and sex hormones, aging process has been reported to
reduce important major sex hormones: mean serum estradiol (E2) in female by 75% while
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only 20% reduction of mean serum testosterone (Labrie, Belanger, Cusan, Gomez, & Candas,
1997). The protective effect of sex hormones on the bone in aged female may be lifted hence
the complications of primary osteoporosis higher in female (Genant et al., 1999).
Secondary osteoporosis
Secondary osteoporosis is applied to the reduction of bone masses that are not related
to menopause or aging process (Gennari, Martini, & Nuti, 1998). Secondary osteoporosis
occurs regardless of the normal aging factor as in the primary osteoporosis hence any age
group could be affected. The reduction of bone mass in secondary osteoporosis could be as a
result of a single or a combination of various conditions (Templeton, 2005).
The following paragraphs are to illustrate important events that lead to secondary
osteoporosis and the clinical manifestations that are may accompany the events. The clinical
manifestations may be valuable in the clinical investigation to narrow down the primary
causative factor of the reduction of the bones’ ultimate strength, which increase the risk of
spontaneous fracture.
Medical condition that is associated with secondary osteoporosis, including
endocrinal and non-endocrinal diseases. In the endocrinal diseases, the disturbances in the
hormonal balance lead to the negative net balance in bone dynamic. An example of
endocrinal deficiency that is associated with osteoporosis is hypogonadism (Rochira et al.,
2006); the condition whereby the sex hormones are insufficient. As the sex hormones are
important in the BMC modulation, the reduction in the hormones causes the disruption in the
bone growth and expansion for the pre-pubertal group, while accelerated bone absorption is
predictable in the adult group (Vanderschueren et al., 2004). Genetic disorder such as
Turner’s syndrome that leads to gonadal dysgenesis (K. Rubin, 1998); removal of the sex
hormones producing tissue as in surgical gonadectomy or chemical castration
(Vanderschueren et al., 2004), would also result-in hypogonadism related osteoporosis. Other
clinical symptoms for hypogonadism include the absence of secondary sex characteristics,
infertility, muscle wasting, and other abnormalities (Patidar, Thakur, Kumar, & Kumar,
Excessive in endocrine hormones is also detrimental to the net bone dynamic. In cases
such as hyperthyroidism, the bone dynamic is accelerated through the effect of thyroid on
both osteoclast and osteoblast. However, the quality of mineralisation is affected hence the
net chronic effect will be the reduction in bone density (Vestergaard & Mosekilde, 2003).
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Other clinical manifestations of hyperparathyroidism in human are fatigue, nervousness or
anxiety, weight loss, palpitations, heat sensitivity, decreased fertility, reduced libido and
sometimes gynecomastia in men (Carlson, 1980; Cooper, 2003; Krassas, 2000). Several
medication/chemicals which are used to treat other non-bone conditions were found to be
detrimental to the bone. The mode of action of those chemicals may not be the same, but the
result is a significant reduction in BMD.
Excessive of certain trace elements such as fluoride was demonstrated deteriorative to
the bone. While dietary fluoride is known to increase calcium retention in bone, the shear
strength of long bone was reduced by 30% (M. Chan, Rucker, Zeman, & Riggins, 1973). The
pathological effect of chronic and excessive fluoride exposure on bovine has been reviewed
by Shupe (1992) which suggested other three main systems are affected by fluorosis: dental,
skeletal and renal system. Clinical features of fluorosis include dental erosion, bony
exostosis, lameness debility, poor production with no age preferences (Patra, Dwivedi,
Bhardwaj, & Swarup, 2000)
Deficiency of certain trace element such as copper long was associated with
osteoporosis as copper is a component of lysyl oxidase that involved in cross-linking of the
collagen in the bone (Rucker et al., 1998). Conversely, bone is not the only tissue that can be
affected by chronic copper deficiency as there are many enzymes depends on copper for the
normal function for examples cytochrome oxidase (erythropoiesis and central nervous
system, gastrointestinal system), super oxidase dismutase (immune system, reproduction) (S.
Chan, Gerson, & Subramaniam, 1998; Fisher, 1975; Percival, 1998; Xin, Waterman,
Hemken, & Harmon, 1991). Therefore, copper deficiency syndromes are usually presented as
a multisystem failure. The clinical manifestations of copper deficiency in cattle may include
anemia, scour, impaired growth, dull hair coat, unthrifty, poor immunity, and reproduction
failure.(Black & French, 2004; Mills, Dalgarno, & Wenham, 1976; Moore, 1991; Smart,
Gudmundson, Brockman, Cymbaluk, & Doige, 1980).
Macro minerals that constitute the bone crystal (calcium and phosphorus) would
influence the strength of the bone. However, the comparison of the degree of mineralisation
of different bony structures to the strength may not be straight forward; Bovine femur (67%
mineral content) has 1.4 times higher bending strength than red deer antler (59% mineral
content), but the force needed to fracture the antler is 2.2 times the force needed to fracture
the femur (J.D. Currey, 1999). Conversely, comparison of the calcium content of the same
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bone may serve as a relative indicator for the bone strength. An increase of 10% of mineral
content of a femur increases the yield strength by 70% (Brear et al., 1990), hence the same
proportion of reduction in strength could be assumed when the bone losses the calcium
content. A classic work by Bocker et al (1934) identified the association of the calcium
supplements in lactating dairy cows with the prevention of various bone fractures (hip, rib
and pelvic). The long bone strength of un-supplemented cows was also found less 90% than
of the supplemented cows group (Bocker, Neal, & Shealy, 1934).
The endocrine system works efficiently in maintaining the narrow range of plasma
calcium level of 8-10mg/dL (Goff et al., 1991) hence the reduction of plasma calcium level in
the face of dietary calcium deficiency may be compensated by mobilising the calcium reserve
in the bone. A prolonged dietary calcium deficit in the face of an increase in calcium demand
such as during the 3rd trimester of pregnancy, continued to the lactation phase may
temporarily expose the bone excessive resorption. Therefore, increases the risk of fracture.
Transient osteoporosis to pregnancy and lactation has been widely reported to be associated
with the incident of low force fracture (Curtiss & Kincaid, 1959; Di Gregorio, Danilowicz,
Rubin, & Mautalen, 2000; Samdani, Lachmann, & Nagler, 1998; Sowers M & et al., 1993;
Spencer, 1979; Stamp, Mclean, Stewart, & Birdsall, 2001).
While the spontaneous bone fracture is a general term to describe the pathologic
fracture, stress fracture is a specific type of non-traumatic fracture, which has no relation with
pathological condition of the bone (J. M. Morris, 1968). Stress fractures could occur when
there are repetitive forces, constantly applied on the bone (Carter, Caler, Spengler, & Frankel,
1981). Those who were involved in high physical stress activities had been identified as the
most likely group to get the stress fracture (Branch, Partin, Chamberland, Emeterio, &
Sabetelle, 1992; Freslon et al., 2004; Matheson et al., 1987). In animal kingdom, stress
fracture has been reported in horses (Kraus, Ross, & Boswell, 2005). It was revealed by Burr
(2007) that bone microdamage, which is an important micro-feature of fatigued bone, could
occur without any prominent high-stress activities. The micro damage accumulates over time
(which exponentiate after the age of 40) and gender is a risk factor for the accumulation
(female accumulate twice as rapid as male).
Osteogenesis imperfect (OI) is another bone disorder that may be presented in animals
as spontaneous fracture. OI is a rare inherited bone disorder caused by genetic disorder,
which may include the gene that encodes the procollagen molecule or the production matrix
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protein. The defected gene (COL1A1 and COL1A2) responsible in producing collagen 1 that
serves as a template for calcium phosphate deposition that strengthens the bone (Rowe, 2002;
Seeliger et al., 2003). Other several non-collagenous matrix proteins that promote mineral
deposition on collagen such as osteonectin and proteoglycan were also depleted in OI
(Termine et al., 1984). The degree of severity of patients with OI may vary from mild to
lethal, but the typical clinical manifestations are the spontaneous fractures of bone and teeth
with variety of other signs such as opalescence teeth, blue sclera, joint laxity (Rowe, 2002;
Seeliger et al., 2003). OI has been reported in many animal species whereby the young
animals were mostly affected (Agerholm et al., 1994; Arthur, Thompson, & Swarbrick, 1992;
Cohn & Meuten, 1990).
1.10 Conclusion
Bone is a special type of tissue that involved and support many important functions. As
hard as aluminium, bone tissue is very dynamic as it has the capacity to model the original
shape in the prepartum period, grow multiple times bigger than the earlier size at birth, or
remodel the current bony structure. The bone dynamic is made possible due to the presence
of BMU that comprises of osteoclast, osteoblast and osteocytes, supported by local and
systemic regulators with the presence of the building block (protein and minerals).
As bones depend on many factors in maintaining its normal functions, it is prone to
become defective should any of the supportive factors fall short. Spontaneous fracture of the
bone which could prevent the bone from performing its movement function is an indicator
that there is a failure of one or a combination of factors to maintain the inherent strength of
the bone. There are many causative agents that could result in lower ultimate strength, but the
site of bone fracture may not provide a clear indicator of which causative agent involved.
The clinical manifestation and the demographic features of cases, as reported by many
researchers, may provide some clues that could be used to narrow down the possible
underlying problem that leads to the spontaneous fracture.
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Chapter 2
Spontaneous humeri fractures in New Zealand dairy population 20072012; a series of 115 cases
2.1 Introduction
Bone fracture is generally known as a discontinuation of bone integrity as a result of
direct or indirect force (McGuigan, 2010). Bone fracture is an important debilitating
condition which causes severe pain and mobility restriction (Gangl, Grulke, Serteyn, &
Touati, 2006; Nichols, Anderson, Miesner, & Newman, 2010). Even though bone fracture is
a treatable condition, the prognosis and the economic aspect of fractures differ according to
the underlying causes, location of fracture, treatment of choices and the species involved
(Crawford & Fretz, 1985)
Bone fracture, based on the underlying causative agent, can be classified into traumatic
or pathologic (Doblaré, Garcıá , & Gómez, 2004; Wiesel & Delahay, 2010). In traumatic
related fracture, an acute direct force is involved, which deformed the bone immediately if
the force exceeded the ultimate strength; or causing micro-damage if the force was between
the yield point and ultimate breaking point. The micro-damages could accumulate and have
been reported to decrease bone tensile strength up to 40% (Burr et al., 1997). Age and gender
were found to be associated with the micro damage accumulation; the crack density
exponentiate after the age of 40 years and females accumulate bone micro damage twice as
rapidly as males (Schaffler, Choi, & Milgrom, 1995).
In pathologic fracture, bone continuity dissociates without obvious prior traumatic
episode suggest that pre-existing pathological bone lesion lower the inherent tensile strength
of the bone. The bone strength can be reduced when: there was an excessive bone resorption
that affected the BMD (Barrett-Connor et al., 2005); inadequate in bone cell production
(Glorieux et al., 2002), pathological remodelling of bone (Dove, 1980); defective in bone
mineralisation (Hoikka, Alhava, Savolainen, & Parviainen, 1982); abnormal growth of bone
cells (Scully, Ghert, Zurakowski, Thompson, & Gebhardt, 2002).
Spontaneous fracture (also known as low force fracture) is a condition of disrupted
bone structure with no apparent involvement of blunt force trauma (Horiuchi et al., 1988).
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While the spontaneous fracture is a common outcome of pathologically compromised bone,
the condition is not exclusive; other healthy groups of human or animal also recorded the
incident. Non-pathogenic spontaneous fractures were also found in baseball players (Branch
et al., 1992), cross-country runners (Freslon et al., 2004), horses (Kraus et al., 2005)
indicating that repetitious high stress physical activity could lead to this type of fracture.
The decrease in bone strength, which increases the risk of low force fracture, had been
previously reported associated with other factors such as:
Nutrition: Chronic deficiency in copper (Rucker et al., 1998), calcium (H. A. Morris,
O'Loughlin, & Anderson, 2010), magnesium (Stending-Lindberg, Tepper, & Leichter,
1993) or excessive in fluoride (M. Chan et al., 1973), phosphate (Huttunen et al.,
Gender: pregnancy and lactation osteoporosis in human (Di Gregorio et al., 2000), gilt
(Spencer, 1979)
Age: rickets (Chapman et al., 2010), hypogonadism in aging (Ahlborg, Johnell,
Turner, Rannevik, & Karlsson, 2003) .
Medication of other disease such as autoimmune (E. Canalis, Mazziotti, Giustina, &
Bilezikian, 2007)
Bone fracture in large ruminant is not a common condition. A four-year retrospective
studies in a large animal clinic in Belgium (Gangl et al., 2006) could merely manage to detect
99 cases. Another eight-year retrospective studies in a large animal clinic in Canada
(Crawford & Fretz, 1985) only manage to include 213 fracture cases. None of the identified
fracture cases were classified as pathologic and spontaneous. Both retrospective studies
suggested, at most, 24-26 cases of large ruminant traumatic fracture could be expected to be
seen in a year by a veterinary practice. The most frequent fractured bone is not unanimous.
Gangl (2006) rank tibia as the most common fractured bone (57% of cases) while Crawford
(1985) reported femur was the most common fractured bone in large ruminant (32% of
cases). The age group, weight and gender play an insignificant role in determining the
frequent fracture site as well as the prognosis (Crawford & Fretz, 1985; Gangl et al., 2006;
Nichols et al., 2010). The season in which the fracture would have happened, however, may
be significant as many researchers observed that the cases were predominantly in spring
(Gangl et al., 2006; Martens et al., 1998; Weston, 2008) which is the busiest season for
synchronised spring breeders.
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A first case report pertaining to humeri fractures in dairy cattle in New Zealand, which
labeled as spontaneous, was reported by Weston (2008). The observed spontaneous fracture,
which involved four cows in their first lactation, occurred within a short duration between
one another (the shortest duration was within a week). Copper deficiency was suspected to
cause the fracture due to the low liver copper level of the case animals. Based on the case
report, the first case cow was euthanized, and the remaining three were dried-off. Out of the
three remaining, one fractured the other humeri and had to be euthanized. Since then, more
reports pertaining to the spontaneous humeri fractures were reported to the veterinarian at
Massey University directly or indirectly (Weston, Thompson, Dittmer, & Abdul Rashid,
We investigate the occurrences of spontaneous humeri fractures' syndrome in New
Zealand dairy cattle from 2007 to 2012. Our aims were to describe the demographic, spatial
and temporal characteristic of the syndrome as we believe that, at the material time; the
syndrome was new and did not occur in random. As reported by Weston (2008), the case
animals were either had to be dried-off or put to sleep, therefore, the impact of the cases on
the dairy cattle enterprise is non-negligible. The motivation of the study was to identify the
most likely causative agent, and the plausible risk factors associated with the spontaneous
fracture syndrome; hence appropriate immediate intervention can be advised.
2.2 Objectives
The objectives of the study were;
1. To describe the incident of spontaneous humeri fractures in New Zealand dairy cattle
from the aspect of individual case attribute, spatial and temporal related distribution
form rearing season 2007/2008 until 2011/2012.
2. To propose the plausible causative agent and the risk factors that may be associated
with the spontaneous fracture.
2.3 Materials and method
2.3.1 Study design
The study was set out to describe the occurrences of the spontaneous humeri fracture
syndrome in dairy cattle population in New Zealand. The description would include the
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animals, spatial and temporal factors that exist within the study period. The observation
period was set for five years starting from season 2007/08 until 2011/12. A season, such as
2007/08, starts from Jun 2007 until the end of Mei 2008.
2.3.2 The respondent
The study started in December 2011 with the announcement made through the DCV
newsletter and group emails regarding the intention to investigate the fracture syndrome.
Many veterinarians, who had been introduced to the subject matter via a case report that was
presented in the NZVA conference 2008, were contacted to nominate possible case farms to
the best of their knowledge. The farmers whose farm had been identified as case farms were
also invited to nominate the other farms that they thought might experience the spontaneous
fracture syndrome in dairy cattle. The aim was to include as many dairy herds in New
Zealand that had the spontaneous fracture syndrome. The intention to conduct the study was
also conveyed via email to a list of veterinarians who had been assisting other studies
performed by researchers and students in Epicentre, IVABS, of Massey University. The farm
owner whose farm had been identified by the veterinarian as the possible case farm, were
contacted through email and phone prior to the questionnaire distribution. Those farmers who
cannot be contacted, the assistances of the veterinarian were sought to inform them regarding
the study.
2.3.3 The case definition
As the spontaneous humeri fracture syndrome was relatively new, there was no standard
case definition available. The case definition for spontaneous humeri fractures in this study
was derived from the case description in the first case series reported by Watson (2008). In
order to include as many possible animals with the syndrome, the definition has been tailored
by including those cases which had not been seen by a veterinarian to increase the case
inclusion. The working case definition for humeri fracture in New Zealand dairy cattle was:
Sudden, severe non weight bearing lameness of the front leg, and
Physical examinations suggest that the bone between the elbow and shoulder is
fractured, and
No sign of external trauma.
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2.3.4 The questionnaire
A questionnaire which comprises of open and closed questions was produced (annex
1) to assist in capturing the herd and individual-level information. The herd level information
included the farm details, herd history, physical factors and herd’s feeding management.
Individual level information included case description, reproductive status at the time of
fracture and the management of the individual cases. The respondents were required to fill in
only one herd-level questionnaire sheets, but the individual-level questionnaire was meant to
be filled for each case animal. The questionnaires were beta-tested by a farmer in the
Manawatu area to eliminate potential ambiguities, before the distribution to the list of the
identified farmers. Distributions of the case questionnaires begun at the end of December
2011 after amendments were made in the questionnaire’s structure and words selection. The
questionnaire kit contained an open cover letter (annex 2); a set of a standard questionnaire
which include the questions on herd and individual level; five extra copies of individual
questionnaire sheets. The mode of questionnaire return was a prepaid, self-addressed
envelope which was inserted in the questionnaire kit.
The respondents were contacted between one to three times with approximately 30
days apart to remind them about the questionnaire. The first contact was made via email and
phone call at the end of January 2012. The veterinarians who suggested the farmer were
contacted after the third reminder at the end of March 2012 to assist the follow-up activity.
2.3.5 Data handling and analysis
The returned case questionnaires were recorded in Microsoft Excel spreadsheet. The
data were explored to check for missing values and transformation of open answers. The
farmers were contacted again through phone to clarify any ambiguities and furnishing the
missing values. When the farmers could not recall the information, the information was
regarded as a true missing value. All exploratory data analysis was undertaken using SAS
version 9.3 using the FREQ and UNIVARIATE procedures (SAS Institute Inc., Cary, NC).
2.4 Results
2.4.1 Descriptive data analysis
The variables used in the study were generally divided into two parts: captured and
derivative variables. The captured variables were the usable information recorded on the
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questionnaire as written by the farmer while the derivative variables were a product of
transformation or mathematical operations of two or more captured variables. Out of the
captured variables, top three variables with missing values were the wean weight; wean age
and the affected leg which recorded the proportion of 56%, 43% and 40 % respectively. Out
of the derivative variables, the cattle walk speed was noticed to have the highest proportion of
missing value, which was 22%.
Figure 2-1: Proportion of missing value on captured variables
Figure 2-2: Proportion of missing value on
the derivative variables
One peculiar aspect of derivative variables was that the missing data proportion
depends on the scale of transformation and the original variable from which it derived from.
An example of this transformation paradox was the derivative variable used to describe the
duration post calving; calving date and case date were needed to produce duration post
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Table 2-1: Derivative variables and its description
Var type
Fracture date-birthday in days
Fracture date-birthday in month
Fracture date converted into
Age of fractured
animals (month)
Age of fractured
animals (days)
Absolute month
absolute calendar month
of fracture
Day post calving
Fracture date-calving date in days
Month post
Fracture date- calving date in
Walking speed
Walk distance/walk time
Rearing season
The observation year. For example;
Rearing season 2011/12= June
2011-Mei 2012
Parity group
The indicator of the reproductive
N-North island/S-
age. If the animals had calved and
in the last trimester of 2nd
pregnancy, they are grouped into
1st parity group.
Region category
Reclassification of region
North island/South
The missing data percentage in the case date was 3% while the missing data
percentage in calving date was 11%. The missing data for duration post calving, which was
derived from the calving date and the case date were not a figure in between 3-11% as
recorded in the parent variables. If the unit of the derivative variables were higher in the
sensitivity, the missing data percentage was higher; day-post calving recorded 14% missing
data while month-post calving recorded 8% missing data as many farmers could only recall
the month of occurrences, not the exact date.
Questionnaires were mailed to thirty farms, which had been identified by the local
veterinarian as the possible farms with spontaneous fracture syndrome. Twenty two farmers
(73%) responded by returning the questionnaire; two refused to participate (7%) on the
ground of not being able to recall the information as it happened quite sometimes, involving
less than two animals and did not recur; the rest potential respondent (20%) did not state the
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Figure 2-3: Trend of the reported cases over 2007-2012
Figure 2-4: The frequency of farm with repeated case
season 2007-2012 (n=22)
Overall, 149 cases were recorded based on the working definition suggested, from 22
farms that responded, over five rearing seasons from 2007/2008 until 2011/12. Out of 149
cases, 115 case details (77%) managed to be recorded in the individual cases' sheet. Case
details captured in seasons 2008/09 and 2010/11 were less than 50% of the total reported case
in respective years, whereas the case details in the other seasons exceeded 70% response. The
reported cases were on the increasing trend (R2=0.7), based on the five-year observation
starting from 2007/08. The spontaneous fracture cases were not a one-off experience. One
farm experienced the spontaneous fracture in four seasons; two farms had recorded three
affected seasons, and seven farms had recorded two affected seasons (fig 2-4).
2.4.2 Animal factors
All 115 animals that fit into the case definition were female, aged between 24 to 40
months. A closer examination on 101 case animals revealed that there were two fairly
symmetrical age group's distributions involved. The first age group which consists of 83%
(84/101) of the observation were aged between 24 to 31 months with mean age was 26.75
(SD=1.60) months. The second age group seemed to have a smaller density (17%, 17/101)
with a range of 36 to 40 months and mean age of 38.35 (SD=1.11) months. No cases were
recorded in dairy cattle aged less than 24 months, between 32 and 35 months and more than
40 months.
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1st age
2nd age
Figure 2-5: Case frequency as a function of age and the summary statistics (n=101)
The affected breeds as recorded in 113 cases were Friesian (23/113, 20%), Jersey
(24/113, 21%) and crossbreed (66/113, 58%). Regardless the breed, the animal quality index
of the case animals as recorded in ‘production worth’ and ‘breeding worth’ is shown in table
2-2. The two indices were highly correlated with the calculated correlation coefficients was
0.96. Based on 98 cases, the production worth was fairly symmetrical (Kolmogorov-Smirnov
p=0.010) with the mean of 117.29 (SD=54.02), median of 120 (q1=84.25, q3=148.75) and a
huge range from -23 to 319. The breeding worth of the case animals was distributed normally
(Kolmogorov-Smirnov p=0.086) with a smaller measure of variability compared to the
production worth. The breeding worth mean was 115.90 (SD=38.37), median of 112.5
(q1=98.5, q3=142.75), and a range between 16 and 226.
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Figure 2-6: Case frequency as a function of cattle
breed (n=113)
Figure 2-7: Case frequency as a function of parity
All 155 cases animal fractures were recorded either in the late pregnancy or had
recently calved. They can also be categorised according to the respective parity group. Parity
0, a group which consists of heifers in the final month of the 3rd trimester constitutes of 3%
(3/115) of the case details obtained. Parity 1, a group of the recently calved cows to their first
calf and possibly pregnant for the second time constitutes the largest portion of the case
animals (83%, 95/115). The remaining case animals were in the Parity 2 group, which consist
of cows in their second calving.
Stratification of the case animals by the post-partum period is shown in fig 2-16. The
calculation of the postpartum period for the first parity was straight forward; the calendar
month of the case minus the calving month. If the animals were in the second parity, the
calculation of the post-partum period started with the second calving to the month of fracture.
Postpartum 0 means, the animal had not calved when the fracture happened. Based on the bar
chart of case frequency as a function of the post-partum period, 88% (93/106) of cases
occurred in the first-4 month’s post-partum.
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Figure 2-8: The distribution of breeding worth (BW) and
production worth (PW) of the case animals (n=98)
Figure 2-9: Scatter plot showing the
relationship between breeding worth and
production worth of the case animals (n=98)
Table 2-2: Summary statistics for the quality indices of the case animals
Breeding worth
Production worth
The case frequency as a function of the observed body condition is shown in fig 2-10.
The body conditions were arbitrarily assigned by the farmer into three ordinal scales: light, if
the animals were under the acceptable weight; average, if the animals were at their suitable
weight; extra, if the weight were above the normal. Three points along the cases' animal
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timelines were selected: before mating, upon return from grazier and before fracture. The
condition before mating indicates the wellbeing of the case animals prior to pregnancy; the
condition upon return from grazier indicates the food availability in the grazier and the body
condition before fracture showed the general health status of the case animals. The three-time
body condition observations could also show the fluctuation of the body weight of the cases
over time. Fig 2-10 shows that 89% (92/103) of case animals before mating; 99% (99/100) of
case animals upon return from grazier; 93% (93/100) of the case animals before fracture had
an average to extra good body condition. The body condition of case animals did not
deteriorate noticeably at any point of their time line. As a comparison to the other animals in
the farm where the case animals were located, 68% of the case animals had been at par with
the overall animals which had been classified as the non-case based on the case definition
while, 7% were better than the farm average (fig 2-11).
Figure 2-10: Case frequency as a function of the observed body condition
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Figure 2-11: Cases frequency as a function of the relative body size to the whole herd (n=98)
The case animals, as well as the other animals in the case farm were raised in the
grazier, which could be the other part of the farm or located in the other area outside the farm
compound. At the age between 20 to 24 months, the animals returned to the farm either by
walking or transported by truck. Fig 2-13 shows that 7% (7/103) of the case animals had been
walked while the rest (93%, 96/103) had been transported from the grazier by truck. As the
animal parity signifies the duration post transportation, parity 2 is further in the timeline as
compared to the earlier parity. If the animal in parity 2 was discriminated due to the longer
duration post transportation, the proportion of case animals transported by truck was still high
(92%, 82/89).
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Table 2-3: The count of affected front leg by the location (n=69)
Region Cat
Herd ID
N-North Island
S-North Island
South Island
Grand Total
Affected leg
Grand Total
The affected humeri for the case animals are shown in fig 2-12. The right-side humeri
recorded a higher percentage of fracture (53%, 37/69) as compared to the left (44%, 31/69) but the
difference may not be significant as the 95% CI of the proportion of the null value is between 0.38
and 0.62.
Figure 2-12: The proportion of affected leg stratified by
the parity (n=69)
Figure 2-13: The proportion of the mode of transporting
case animals stratified by the parity (n=103)
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2.4.3 Temporal factors
The time line of the spontaneous humeri fracture cases over the five rearing season
starting from season 2007/08 is shown in fig 2-14. The timeline plot shows that the
spontaneous humeri fractures had a distinctive seasonal pattern; it occurred in every spring to
summer except for season 2008/2009. Regrouping of the cases based on the absolute month
of occurrences is shown in fig 15. The cases appeared in July until February, peaked in
September (35/105) and October (34/105), declined by half after the peak month in every
following month.
Figure 2-14: Time series of the spontaneous humeri fracture cases in dairy cattle from 2007-2012 (n=115)
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Figure 2-15: Case frequency based on the absolute
month of occurrences (n=105)
Figure 2-16: Case frequency as a function of postpartum period (n=106)
In relating to the drought experience of the case farms, 77% (88/115) case animals
were from the farm which had recorded severe droughts that affect the vegetation in the farm
within the observation period (fig 2-17). As the droughts were not a regular yearly event in
the affected farms, the frequency in relation to the prior drought experience was produced
(fig 2-18). The post drought to fracture duration for 88 case animals that were located in the
drought-affected month ranged from 4 to 48 months, with the mod value of eight months.
Figure 2-17: Cases frequency
stratified by the prior severe drought
experience (n=115)
Figure 2-18: Cases frequency as a function of the duration between
the last month of drought and the case occurrences (n=88)
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2.4.4 Spatial factor
The case farms were centralised in six farming regions (table 2-4): Auckland, Bay of
Plenty, Waikato, Manawatu, North Otago and Canterbury, whereby Waikato recorded the
highest case count (64%) over the observation period. Based on the specific district in which
the spontaneous humeri fracture occurred in dairy population 2007-2012, Morrinsville
recorded the highest (27.5%, 41/149) while Pukekohe had the lowest (0.7%, 1/149) count.
Table 2-4: Count of cases based on the rearing seasons and the location
Region cat
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
North-North Island
South-North Island
South-North Island
South-North Island
South-North Island
South Island
South Island
Farming Region
Bay of Plenty
North Otago
Rearing season
Total Case
2007/ 2008/ 2009/ 2010/ 2011/
cases %
cat %
2008 2009 2010 2012 2012
Te Puke
13 8.7%
27 18.1%
18 12.1%
Te Aroha
Te Aroha
12 8.1%
13 8.7%
Palmerston North 0
10 6.7%
149 1.00 100% 100%
The distribution of case farms is shown in fig 2-19, 2-20 and 2-21. Based on the farm
cluster, the farming regions were re-categorized for gross comparisons; to see the persistence
of risk factors in the case farms.
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Figure 2-20: The spatial cluster of case farms in North
Figure 2-19: Spatial distribution of the case farms
showing the geographical clustering of case farms into
3 major area: North-North Island, South-North Island
and South Island
Figure 2-21: The spatial cluster of case farms in South
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Figure 2-22: Case frequency as a function of age stratified by
region (n=101)
Figure 2-24: Case frequency as a function of post drought duration
to case stratified by region (n=88)
Figure 2-23: Case frequency as a function of
post-partum period stratified by the region
Figure 2-25: Case frequency based on the
absolute month of occurrence stratified by
region (n=105)
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2.4.5 Spatial influence on animal factors
The farm locations were categorized according to the gross geographical location to
investigate the similarities in case animal's attributes in different spatial factor. Stratification
of the age of case animals by region that is shown in fig 2-22 stating the first age group of
case animals(between 24 and 31 months) was common in all regions but the second age
group of case animals (from 36 to 40 months) were dominated by the North-North Island
With regards to the post-partum period (fig 2-23), North-North Island (NNI) region was the
only region that recorded late pregnancy spontaneous fracture in heifers (3/106) and
contributed to the high case count in the first four-months post-partum. The South-North
Island (SNI) region post-partum duration before fracture’s range was as wide as the NorthNorth Island (range between one and eight-month post-partum) with the highest count was
recorded in the 3rd months (41%, 7/17) . While the South Island (SI) region cases were
recorded in the first three-month post-partum with the highest month was the 1st month (58%,
The case frequency post draught experience, stratified by the region (fig 24) revealed
that none of the South-North Island cases animals had experienced severe drought despite
23% (27/115) of the case animals were from that area. Most (92%, 81/88) of the drought
affected case animals were located in the North-North Island.
Stratification of the case animal’s parity group by the region (fig 2-27) revealed SNI
and SI had recorded cases that were in the first parity only. The NNI region recorded cases in
all three parity groups with the 1st parity remains as the highest proportion (76%, 66/86).
The absolute month in which the case occurred, stratified by the region can be seen in
fig 2-25. Generally, the cases' occurrences were distributed over a few calendar months of the
year. In NNI, a higher count of cases (70%, 59/85) was observed in September and October.
The SNI region, however, recorded an earlier peak of count (92%, 11/12) than NNI, which
was in August and September, while the SI region’s peak counts (63%, 5/8) were recorded
the latest in the calendar months (October and November) among the three regions.
The breed of the case animals based on the region category is shown in fig 2-26.
Based on the breed proportion comparison between the North-North Island (NNI) and the
South-North Island (SNI), the difference in the breed proportion was by chance only as a
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direct comparison of the breed proportion 95% confidence interval in the North-North Island
overlapped with the same breed in the South-North Island (Breed/Region/95%CI):
Jersey/SNI/0.04-0.36; Friesian/NNI/0.14-0.31; Friesian/SNI/0.14-0.56). Breed proportion
comparison against the South island was not produced as only one breed was recorded for the
case animals: crossbreed.
Figure 2-26: Proportion of cases in each region
stratified by breed (n=113)
Figure 2-27: Proportion of cases in each region
category stratified by parity (N=115)
The quality index of the case animals by the region category is shown in fig 2-27,
with the summary statistics in table 2-5. From the aspect of BW, the NNI region had the
highest measure of central tendency (mean=121.43, median=124.5) and the widest range
(from 17 to 226). SNI appeared to have the largest BW variability (SD=50.62) while SI had
the best measure of precision (SE= 4.19). From the aspect of PW, the SI region recorded the
highest mean; NNI region recorded the highest measure of central tendency (median=127),
variability (SD=58.91) and range (from -23 to 319). Conversely, the differences in the PW
and BW statistics between regions may be due to chances alone as the 95% confidence
interval of the means overlapped.
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Figure 2-28: Breeding worth and production worth of the case stratified by region category
Table 2-5: The summary statistics of the quality indices of case animals by the region (n=98)
The timeline of case animals’ body condition according to the region is available in
fig 2-29. Generally, the case animals had achieved a desirable (average and extra good) body
condition at every point of time under study except for SI region before mating as
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83%(10/12) had been observed as underweight. Nevertheless, the body condition of the case
animals in the SI region had improved as they returned to the case farms and before the
fracture happened. As a comparison to the whole animals in the farm (fig 2-30), majority of
the case animals in NNI (75%, 57/76) and SNI (80%, 8/10) maybe indistinguishable from the
non-case. The case animals in SI, however, were noticed to be below the farm average
despite having an average weight score before the fracture as pictured in fig 2-30. This could
mean the non-case animal in the SI were having an extra good overall score.
Figure 2-29: Cases proportion as a function of region stratified by the observed body condition
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Figure 2-30: Proportion of cases by region stratified by
the relative body size to the whole herd (n=98)
Figure 2-31: Proportion of cases by region stratified by
the affected humeri (n=69)
Figure 2-32: Proportion of cases by region stratified by the mode of heifer's transportation (n=103)
The proportion of the affected side of the leg appeared no different between NNI and
SNI, but SI recorded 100% (12/12) cases involving right leg (fig 2-31). Transportation of
heifers using a truck as the main method to move the case animals from their respective
grazier was unanimous in the regions (fig 2-32).
2.4.6 Temporal trend on animal factors
The type of breed affected by the spontaneous fracture stratified by the rearing season
is shown in fig 2-33. Contrary to the earlier pool data (fig 2-6) that showing the count of
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cases, in which cross breed animals had twice as many case counts than the other pure breed;
no breed appeared to be consistently dominant in every rearing season over the other in all
the observation periods of five rearing seasons, even though the cross breed consistently
appeared in all observation year.
Figure 2-33: Proportion of cases over observation
year stratified by breed (n=111)
Figure 2-34: Proportion of cases over observation
year stratified by parity (n=115)
Stratification of the case animals’ age of fracture by the rearing season (fig 2-35)
revealed that the involvement of the second age group (n=17, mean age= 38 months, age
range= 36-40 month) was a new phenomenon as it occurred during the final observational
rearing season of five. A further rearing season stratification of the case animals by the parity
group (fig 2-34) revealed that the second age group were actually on their second parity,
which comprises of 22% (17/78) of the cases in season 2011/12. Parity 1 was seen as the
common and important parity for the spontaneous fracture as the proportions of parity 1 in
every season were no less than 78%.
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Figure 2-35: Case frequency as a function of age stratified observation year (n=101)
The scatter plots of the case animals’ quality index (breeding and production worth)
against the rearing seasons is shown in fig 2-36. A linear trendline using the least square
method was fitted into the plot to examine the seasonal trend of the quality index. The PW
plot shows that the fitted mean of PW in every observational rearing season (113.45) were
constantly high from the beginning of the observation (R2=0.0006). The BW of the case
animal, even though it had already shown a high fitted mean from the beginning (90.99),
grew by 7.4 unit on the following rearing season (R2=0.05).
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Figure 2-36: The trend of animal quality indices over five observation years
The timeline of case animals’ body condition according to the rearing seasons in
which the spontaneous fracture happened is available in fig 2-37. Generally, the case animals
had achieved a desirable (average and extra good) body condition upon return from the
grazier but dropped into the average score before the fracture happened. This may be due to
the fact than the case animals were pregnant upon return; and had given birth or started
lactating before the fracture; hence the body conditions upon return from grazier were seen
superior than before the fracture happened. As a matter of comparison with the whole herd,
more than 50% of the case animals in every rearing season were at par or greater than the
herd average (fig 2-38). The proportion of affected side of the leg also appeared no obvious
trend over the observational duration (fig 2-39).
The involvement of a truck as a transportation means for heifers from the grazier to
the case farms was consistent throughout the observation period. Fig 2-40 shows that only on
the last observation year, the case animals which did not use truck for the heifer
transportation were included in the case count and a small fraction (10%, 7/73).
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Figure 2-37: Proportion of cases by observation year stratified by the observed body condition
Figure 2-38: Proportion of cases by observation year
stratified by the relative body size to the whole herd
Figure 2-39: Proportion of cases by observation year
stratified by the affected humeri (n=69)
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Figure 2-40: Proportion of cases by observation year stratified by the mode of heifer's transportation (n=103)
2.4.7 General farm factors
In general, the animals in the case farm had to walk daily to the milking platform to
be milked. The summary statistic of the walking distance and speed is shown in table 2-6.
The case frequency as a function of the average daily walk distance, four weeks prior to the
fracture is revealed in fig 2-41. It seemed that the fracture cases were independent of the
average daily walk distance as the plot pattern was random. The case frequency plot against
the walking speed, however, as seen in fig 2-42 revealed an increasing trend. A linear plot
fitted using the least square method shows that 12% of the variation in the case frequency can
be explained by the walking speed (R2=0.12).
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Figure 2-41: Case frequency as a function of the
average daily walk distance in a month prior to the
fracture (n=95)
Figure 2-42: Case frequency as a function of the
average daily walking speed within a month before
fracture (n=90)
Table 2-6: Summary statistics of the walk speed and distance of the case animals within a month prior to the fracture
Walk speed (km/hr)
Walk distance (metre)
The feeding and supplementation profile of the affected farm were included in the
study as to investigate the connection between the case incident and the feed in different
parity. In this study, the proportion of cases in the first parity was noticeably higher (83%,
95/115) than the other parities and the parity group of higher than 2 were not affected. The
feeding profile of case farms can be divided into four groups: calf, non-pregnant heifer,
pregnant heifer and lactating cows. The summary of the proportion of case farms’ basal feed
in different animal groups is shown in table 7. It was noted that all animal groups had been
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fed with rye and clover as the main roughages. The other basal diet which exceeding the 50%
mark (i.e. common in more than half of the case farms) were grass silage in pregnant heifer
(68%) and lactating cows; maize silage ( 55%) and PKE (68%)in lactating cow. Figure 44
shows the graphical comparisons of the basal diet between the age group in the case farms
Figure 2-43: Nutrient supplement of different group in the case farms (n=22)
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Figure 2-44: Basal diet of different age group in the case farms (n=22)
The summary of the proportion of case farms’ mineral supplementation in different
animal groups is shown in table 2-7. The supplemented minerals which exceeding the 50%
mark (i.e. common in more than half of the case farms) were copper (64%), calcium (55%)
and magnesium (77%) in the lactating cows. Figure 2-43 shows the graphical comparisons of
the mineral supplementation between the age group in the case farms (n=22).
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Table 2-7: The feeding and mineral supplementation profile for the case farms; the proportion figure stated in the
table indicates the number of farms which has been given the listed item out of 22 case farms. If the figure stated 0.5,
Green feed oat
Grass silage
Maize silage
50% of the case farms had given the item to all animas in the farm according to the age group.
2.4.8 Comparisons of study data with known references
The quality index of dairy cattle, as published by DairyNZ was compared to the
quality index captured in the study and can be seen in figure 2-45. It was learned that the
median of the case animals’ quality index of were significantly higher (Wilcoxon rank test
p<0.001) than the national average in 2011.
Figure 2-45: Comparison between case animals’ quality indices with the national reference 2011 produced by Dairy
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2.5 Discussion
A total of 149 cases was reported by 22 respondents whose farm had been affected by
spontaneous humeri fracture in five years observational studies, based on the proposed
working definition. The figure was 37 times larger than the initial case report produced by
Weston (2008). Even though the total number of affected cows is small as compare to the
total cows in New Zealand, which is exceeding 4.5 million in 2011 (DairyNZ, 2011b), the
facts that it had never reported in dairy cattle population elsewhere produces no precedents on
how to effectively manage the problem. The trend of the incident over five-year observations
(R2=0.7) is distressing as the case count in the following years could potentially rise
exceeding the last count in 2011/12, which was 83 cases. The case culling rate of 50% with
the survivors had to be dried-off (Weston, 2008) justified the need to investigate the unique
fracture syndrome as it produced nothing but loses to the affected dairy enterprise.
2.5.1 The case definition
With reference to the first case report by Weston (2008), a working definition that
matched the earlier description of case animals was produced. Any cattle would be
considered as a case if the following condition were met:
sudden onset and severe non-weight bearing lameness on the front leg, and
physical examinations suggest that the bone between the elbow and shoulder is
fractured, and
There was no sign of external trauma.
We were aware that the case definition could be more specific by including only cases
that were physically examined by the veterinarian, but the sensitivity of the definition would
be tremendously reduced as not every fracture case could be attended by veterinarians
(Weston, 2008). Based on the case details we gathered, only 58% (67/115) were seen by
veterinarians. Nevertheless, we are confident that fractured long bone in large ruminant is
easy to diagnose as it impede the animals’ movement (Nichols et al., 2010), and as the
affected animals may undergo ‘home kill' to salvage the edible part, the fractured bone can be
2.5.2 The questionnaire
The questionnaire (annex 1) was constructed on mixed formats that combined the
probing and open questions. The open questions or comments were meant to allow additional
information to be reported besides the fixed variables in the questionnaire. However, not all
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variables were reported in this paper, especially the herd factors as it was prepared for the
continuation of the current study such as case-control study.
The information bias that resulting from incomplete or missing information may happen in
this study, especially with these variables (with the missing value percentage, n=115): wean
age (56%), wean weight (43%) and affected leg (40%). In order to reduce information bias,
the respondents were contacted after the questionnaire submission to further explain their
responses. However, further explanations were not asked if the respondent could not
remember the details as to reduce the potential recall bias. The other variables in the study
(fig 1) recorded satisfactory responses.
2.5.3 The results
The study was conducted to find risk factors that were consistently existed before, and
during the fracture happened. The risk factors were grossly divided into three major groups
(individual, time, and place) in line with the convention of reporting sentinel event (Grimes &
Schulz, 2002; Kempen, 2011) as to the best of our knowledge, little is known about the
demographic features of the spontaneous humeri fracture syndrome in dairy population.
2.5.4 Temporal factor
In general, the time line of the spontaneous fracture cases (fig 2-14) suggested that
there was a seasonal pattern of the case. Over the five-year observations, the cases
consistently appear in the second half of the affected years. Stratification of cases according
to the absolute calendar month confirmed our suspicious as the case appeared as early in July,
and peaked in September and October. With the reference to New Zealand’s season, the cases
appeared in spring until summer, which was consistent with the common season of fracture
cases elsewhere observed by Martens (1988) and Gangyl (2006). In relating to the widely
practiced dairy management (DairyNZ, 2011b), spring is the season when pregnant cows start
to calve and a new lactation cycle would begin.
Out of 22 farms that responded, 45% (10/22) had a repeated episode of spontaneous fracture
in different years (fig 4) suggesting that the spontaneous humeri fractures in the case farms
had the tendency to recur. Those case farms (table 4), which had been affected in the final
observation year (2011/12), 56% (10/18), was affected for the first time. Judging from the
repetitive tendency of the affected farms and the involvement of new farms, it was speculated
that the risk factors were still present in the affected farms, and in the other presumably
unaffected farms.
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2.5.5 Spatial factors
The spatial distribution of the case farms is shown in fig 2-19, 2-20 and 2-21. The
details of the location are available in table 2-4. Regardless the administrative boundaries, the
case farms seemed to cluster in the northern part of the North Island, the southern part of the
North Island and the middle part of the South Island, hence the case farms were regrouped as
we were interested to know the persistence of the identified risk factor in the cluster of case
farms. The reasons of the clustering of case farms remain unknown. If the remaining ten nonresponding farms were included, the cluster may still have looked the same as three nonresponding farm are located in Bay of Plenty while the rests are located in Waikato.
2.5.6 Animal factors Breed
A crude evaluation on the cases’ breed in fig 2-6 revealed that case counts in
crossbred was twice as high the individual pure breeds. The New Zealand dairy breed
breakdown (DairyNZ, 2011b) shown that the representation of the recorded case breeds in
New Zealand was as followed: crossbreed (38.9%), Jersey (12.4%) and Friesian (40.0%). The
findings clearly suggesting that the breed differences in case count was not influenced by the
overall breed composition as if that were the situation, the proportion of cases in Friesian
would be similar to the Crossbreed.
Stratification of case count by the region category (fig 2-26) which indicates
crossbreed constitute more than 50% of the case count, concurred with the crude estimation
of the overall case-breed proportion. Conversely, the stratification of cases against the rearing
seasons (fig 2-33) revealed that crossbred was not always had the highest proportion.
Nevertheless, the 95% CI of the breed proportion revealed the crossbreed contribution
towards the annual cases was homogenous. The proportion of each breed that became the
case in the observational period from 2007-2012 (except 2008) were: Crossbred (67%, 39%,
60%, 65%), Jersey (0%, 52%, 40%, 13%), Friesian (33%, 10%, 0%, 22%). The high overall
count of crossbreed that became the case was contributed by the count of cases in season
2011/12 (50/77).
Distinctive features regarding the crossbreeds in New Zealand are: they have a live
weight across the ages that are higher than Jersey but lower than Friesian, and (on average)
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were known as a higher producer of milk volume and milk fat than other breeds (DairyNZ,
2011b). Breed dominations in fracture cases were also observed in many fracture-related case
series (Martens 1998, Gangyl 2006). In summary, breeds may be an important predisposing
factor to the spontaneous humeri fractures and in New Zealand situation, crossbreed may be
at a higher risk. Quality indices
New Zealand dairy farmers in general, adopt performance indicators produced by
NZAEL that are scaled into a 4500 kg DM/year as a unit of feed (NZAEL) and reported
yearly in the New Zealand Dairy Statistics (DairyNZ, 2011b). Based on the information on
the NZAEL info sheet, BW is a comparative ranking system that describes a cow’s genetic
ability to produce a profitable replacement. There are three major components (in a different
weight contribution) that included in the calculation of BW: ancestry information, own
lactation performance and progeny information on seven traits (four traits that increase BW:
protein, milk fat, fertility, residual survival; and three traits that decrease BW: milk yield, live
weight, somatic cells). While the contribution of each component varies with the increase in
the lactation number, the ancestry information is always the biggest component of BW. A
cow with a BW of 100 is expected to produce $50 extra profit per unit feed than a cow with a
BW of 0, through the more efficient breeding daughter. On the other hand, PW is a ranking
system that describes a cow’s own ability to be a profitable and efficient lifetime producer;
not what she is expected to pass on to the offspring. The component that made up the PW is
similar to BW but the biggest contribution came from own lactation performance, which
consists of four traits (traits that increase PW: protein, milk fat; and traits that decrease PW:
milk yield and live weight). A cow with PW of 100 is expected to produce $100 extra profit
per unit feed that a cow with PW of 0.
In this study, the case animals had a median (range) BW of 116 (16 to 226) and PW
of 120 (-23 to 319). Stratification of the performance indicators according to the region
category (tab 2-2) shows that the 95% confidence interval of the mean in each region
overlapped. Hence it can be concluded that the performance indicator of the case animals in
every region category was homogenous. Comparison of the performance indicator with the
national average (DairyNZ, 2011b) of cows’ BW and PW in 2011 (fig 2-45) using Wilcoxon
rank sign test revealed that the case animals had a significantly higher median score
(p<0.0001). The national average of the performance indicators in 2011 was used as a
comparison because 70% of case details (77/111) were recorded in the year 2011/12, and as
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the performance indicator is on the increasing trend (DairyNZ, 2011b), comparison were
made with the highest national average. The temporal trend of the case animals’ performance
indicator as shown in fig 2-36 suggesting that the case animals PW was consistently high
(R2=0.0006) and BW increased by 5% (R2=0.05) throughout the five-year
period. As the case animals BW and PW were found to be consistently and significantly
higher than the national average, they could be risk factors to the spontaneous humeri fracture
syndrome in dairy cattle in New Zealand. Age, parity and duration post-partum
Out of 155 case details obtained from 22 affected farms, none were male. Genderrelated event would plainly suggest that there were elements that the other gender (male) does
not possess which lower the risk of getting the spontaneous humeri fractures' syndrome.
Previously reported case series of bone fractures in large animals (Crawford & Fretz, 1985;
Gangl et al., 2006; Nichols et al., 2010) did not regard gender as a common or important risk
factor for bone fracture in their observation. Gender-related fracture, however, was described
in human and swine population. In human, the increased risks of osteoporosis-related
fracture were mainly post-menopausal (Ahlborg et al., 2003), and during pregnancy and
lactation stage (Di Gregorio et al., 2000). Post-menopause’s higher risk of fracture is related
to the primary osteoporosis whereby the natural reduction of oestrogen has been identified
associated with the event; while lactation osteoporosis is associated with a sudden increase in
calcium demand that was met by the excessive mobilization of calcium reserve in bone. In
swine, as described by Spencer (1979), marginal ration of calcium (5%) from weaning until
the lactation stage produced osteoporotic sows in six weeks of lactation.
In this study, the case animals were relatively young whereby 83% (84/101) and 17%
(17/101) were between 24 to 31 and 36 to 40 months old respectively. Hence, comparison
with the post-menopausal osteoporosis in human may not be appropriate.
Another important feature of the case as reported by respondent was all the case
animals were either in the late pregnancy, lactating or pregnant and lactating. The proportion
of cases in the first parity (95/115, 95% CI: 0.75-0.88) was significantly higher than in the
second parity (17/115, 95%CI: 0.09-0.22) or those pregnant heifers (3/115, 95%CI: 0.010.07). No cases were recorded beyond the second parity. The significantly higher case count
in lower parity is uncommon in many dairy cattle common conditions that affect mobility
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such as lameness (Bicalho, Machado, & Caixeta, 2009) or heel erosions (Chapinal, Baird,
Pinheiro Machado, von Keyserlingk, & Weary, 2010).
Stratification of the case animals by the month post-partum, regardless the parity,
revealed that 88% (93/106) of those cases happened within the first four month of lactation.
The first four-month post-partum is the duration for high milk production (Garcıá & Holmes,
2001; Wood, 1967). Therefore, it is postulated that the spontaneous fractures in dairy cattle
were in line with the period of high milk output, which indirectly correlates with the calcium
demand. Spontaneous fracture cases in the pre-partum period, even though the percentage
was small (3%, 3/106), serve as an indicator that the bone calcium level was extremely low to
compensate the dietary calcium to meet the developing foetus requirement in the third
trimester which is estimated between 2.3g/day (gestation day = 190) and 10.3g/day (gestation
day =280)(House & Bell, 1993). Body condition
Body condition of dairy cows at any point of time is a general indicator of the past
nutritional (Hady, Domecq, & Kaneene, 1994) or the health status (Heuer, Schukken, &
Dobbelaar, 1999; Ruegg & Milton, 1995). Deficiency in feed or the feed quality usually can
be translated into a lower body condition score (Burkholder, 2000). The presence of diseases
such as internal parasitism may also lower the body condition even though the feed quality
issue was non-arise (Sykes, 1994). The commonly used body condition score has five
categories ordinal scale with the highest score of 5 indicating fat, while the lowest score of 1
indicating thin (Edmonson, Lean, Weaver, Farver, & Webster, 1989).
In this study, the body scores of the case animals were recorded in three different
times whereby the case animals would normally be seen by the handler to reduce the
information bias: before mating, upon return from grazier and during the fracture happened.
Individually, the recorded body score may indicate the past state of the case animals, but
together, they may serve as an indicator of the fluctuation of the body condition over an
extended period of timeline. However, instead of using the common five score scale by
Edmonson et al (1989), a simpler three ordinal score scale (light, average, extra good) were
employed in this study with the categories that are generally known by New Zealand dairy
farmers (based on the feedback received when we beta-tested our questionnaire on a farmer
in Manawatu region). The lowest score (light) serves as an indicator that the case animals
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were below the acceptable weight to the occasion. The other two categories were the
acceptable weight to the occasion but ‘extra good’ means the animals were overweight.
The timeline of case animals’ body condition according to the rearing seasons in
which the spontaneous fracture happened is available in fig 2-10. Generally, the case animals
had achieved a desirable (average and extra good) body condition upon return from the
grazier but a noticeable drop from extra good to the average was observed before the fracture
happened. This may be due to the fact than the case animals were pregnant upon return; and
had given birth or start lactating before the fracture happened, hence the body conditions
upon return from grazier were seen superior than before the fracture happened. Similar
change in the body condition scores relative to the parturition in normal cows was observed
by (Dewhurst, Moorby, Dhanoa, Evans, & Fisher, 2000). As a matter of comparison with the
whole herd, this study found that more than 50% of the case animals in every rearing season
were at par or greater than the herd average (fig 2-38) which means physical appearance may
not be able to discriminate the case from non-case.
The importance of the observations over the body weight which were recorded as a
categorical score was to determine whether overweight factors consistent with the fracture
cases. It was learned from the study that only 14% (14/100) of case animals were overweight
hence weight may not be a good predictor for the spontaneous humeri fractures. Body weight
is regularly used to describe the overall clinical symptom of disease condition. For example,
in cases of ruminant copper deficiency, the case clinical description usually included growth
retardation, lower immunity, scour, which collectively may lower the weight gain
(Hidiroglou, 1980; Suttle, 1986) while calcium deficiency effect on the weight gain during
the growing stage may go unnoticed (USDA 1954).
The affected side of the leg (humeri) were included in the study to investigate the
predilection site for the spontaneous fracture. Earlier study by Neveux et al (2006) revealed
that the weight distribution between fore and hind was not significant even though the
forelimb consistently recorded handled a higher proportion of body weight. The ratio of
weight distribution between front and hind of dairy cows were 54:46 while the weight
distributions on the individual limb were as followed: right front ( 27.7-29.4%), left front
(26.0-26.3%), right back (23.4-25.2%) and left back (21.7-22.5%) (Neveux, Weary, Rushen,
von Keyserlingk, & de Passille, 2006). In this study, only the front limbs were seen affected
in which 44% (31/69) was recorded on the left and 53% (37/69) was on the right sided.
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Nevertheless, the differences were not significant as the 95 % CI for proportion of the
affected leg overlapped with the null value (95% CI for null was 0.38 to 0.62). Stratification
of the affected limb by the respective case farms (table 2-3) revealed that only two farms had
recorded a noticeable unilateral high count of cases: farm 12 with five cases of left leg with
no cases involving right leg, and farm 20 with 10 cases of right leg with no cases involving
left leg. Stratification of the affected limb by the year of occurrence (fig 2-39) revealed the
affected side of the front leg had no obvious temporal trend on the preferred site. It would
appear that the fractured humeri may be random but caution has to be exercised to the
conclusion as the missing value for the leg variable is quite high (40%), hence information
bias may occur.
As the case animals were raised elsewhere during the growing stages and returned to
the case farms at the age of 20-24 months, the return activity believed to be important as the
return heifer activity happened prior to the occurrence of 83% (84/101) of the cases in the
first age group (24 to 31 months). If case animals in the 2nd parity were excluded on the
ground that the transportation activities had occurred for sometimes, as much as 92% (82/89,
SE=0.05) of the case animals at risk had been transported by truck. The 95 % CI for the
proportion of the transportation by truck did not overlap with the null value (95% CI for null
was 0.40 to 0.61), hence the transportation by truck may be significant. Stratification of the
means of transporting heifers back to the farm by the region (fig 2-32) and year (fig 2-40)
showed a consistently high trend of the truck involvement. Therefore, transportation of heifer
using a truck may be an important risk factor to the spontaneous humeri fracture.
2.5.7 General farm factors
As the accumulation of micro damage as a result of repetition of stress on the bone
could lead to the weakening of the bone strength (Fyhrie et al., 1998), we investigated the
effect of the physical activities of the case animals in four weeks prior to the fracture. The
physical activity parameters of interest were the walk distance and the walk speed of the case
animals. Fig 2-41, in which the case frequency was plotted against the average walk distance
underwent by the case animals, shows a random pattern. Therefore, it could be stated that the
average daily walk distance in four weeks prior to the fracture was not consistent with case
animals' count. The walk speed of the case animals in four weeks prior to the fracture (fig 242) shows an increasing trend of case frequency with the increase in the walk speed. A fitted
linear trendline using the least square method showed 12% variation in the case frequency
could be explained by the increase in the walk speed four weeks prior to the spontaneous
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humeri fracture (R2=0.12). Rubin et al (1982) found that increased in the moving speed could
increase the micro strains on the long bones (C. T. Rubin & Lanyon, 1982), hence it could be
stated that the increase in walk speed of the case animals may be a risk factor for the
spontaneous fracture syndrome dairy cattle. Drought
Water stress is known to have effect on the dry matter yield but the chemical
compositions usually remain unchanged (Karsten & MacAdam, 2001) hence nutritional
deficiencies as a result of drought are mainly as a consequence of the reduced feed
availability. We investigated the effect of drought on the count of case animals. As the
droughts were not a regular yearly event in the affected farms, the count of cases in relation
to the prior drought experience was produced. In this study, it was revealed that 77%
(88/155) of case animals were located in drought affected farms (fig 2-17). Further
investigation of the post draught fracture event (fig 2-18) revealed that the duration between
the last month drought to the month of fracture ranged between 4 to 48 months (mod=8
months). The finding suggested that there was a long lag between the recorded drought and
the fracture event hence it is doubted that the drought had a meaningful contribution to the
case. The body condition score (BCS) of the case animals that were located in the drought
affected farms were majority (94%, 74/79) on the desired level (average and extra good),
support the thought that the recorded drought had little impact on the case animals. Different nutritional profile
Feeding the dairy cattle is a critical area as it represents 27% of the total operating
cost of a pastoral based rearing system in New Zealand(DairyNZ, 2011a). Therefore,
strategizing the feeding regime that would increase profit has been a priority in dairy
enterprises by the introduction of supplementary feed to the pastoral dairy system (Deane,
1999; Macdonald, 1999). Supplementary feed would not just be providing a low-cost energy
source to dairy cattle (E.S. Kolver, Roche, Miller, & Densley, 2001), it can be used to break
the pasture feed barrier set by the weather related low dry matter yield (Gray & Lockhart,
1996). The feeding and supplementation profile of the affected farms was investigated in the
study in an attempt to link the feed with the fracture cases as the nutritional element deficit
have been implicated in many previous studies (Weston, 2008).
The feeding profiles of the case farm were divided into four animal groups: Calf
(newborn to six months), non-pregnant heifer (6 to 15 months), pregnant heifer (15 to 24
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months) and lactating cow (>24 months). Whereas the first three feedings profiles were not
repetitive as the animals grow older, the last feeding profile (lactating cow feeding profile)
was repeated in each breeding cycle.
Basal diet of the 22 case farms which recorded a total of 149 fracture cases is shown
in fig 2-44 and table 2-7. It was learned that the main basal diets in all 22 case farms were rye
and clover. The other basal diets which were common in more than half of the case farms
were grass silage in pregnant heifer (68%), grass silage in lactating cows (86%), maize silage
in lactating cows (55%) and PKE in lactating cows (68%). Mineral supplementation profile
of the 22 case farms is available in fig 2-43 and table 2-7. The mineral supplement that was
common in more than 50% of the case farms were: copper in lactating cows (64%), calcium
in lactating cows (55%) and magnesium in lactating cows (77%). The findings as illustrated
in radar charts (fig 2-43 and 2-44) indicate that the lactating group received a better ration
amongst the four animal groups.
The lactating group received a better ration possibly because of the additional
requirement for energy and minerals to support the lactating phase (E. S. Kolver & Muller,
1998). The ration differences observed in the study may also explain the distinctive features
of the spontaneous humeri fracture syndrome which was very high in the first parity (83%)
then reduced greatly in the second parity (15%) and none in the subsequent higher parity. It is
suggested that the nutrition content in the growing stages did not prepare the bone for the
normal dynamic of bone remodeling during in the final trimester to meet the foetal growth
and in the lactation stages (Braithwaite, 1983). The basal diet could only supply between
0.42% (rye) to 1.19% (clover) of calcium in dry-matter of feed (Harrington, Thatcher, &
Kemp, 2006) with a maximum absorption efficiency of 66% (Braithwaite, 1983). In the 3rd
trimester, the amount of calcium needed for foetal growth is an additional 2.3g/day (190th day
of pregnancy) to 10.3g/day (280th day of gestation) (House & Bell, 1993) and the lactation
calcium requirement varied is between 1.22 to 1.45 g/kg milk (National Research Council,
2001). If the calcium deficit in the feed were prolonged, calcium from the bone will be
mobilised to meet the demand of maintaining the narrow plasma calcium level between 810mg/dL (Goff et al., 1991). In the second and subsequent parities, the susceptible animals
were getting a better nutrition supplement (calcium, magnesium and copper) from the
previous lactation cow ration hence it was speculated that the lactation ration had prepared
the bone for the next massive bone remodeling in the lactation stage. The lactation ration may
not be able to address the bone calcium extraction appropriately in the first parity probably
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because of the expected negative net balance of bone calcium in the early lactation stage
(Braithwaite, 1983; Oliveri et al., 2004). Additional calcium in the feed during the early
lactation stage may be of less beneficial as additional vitamin D is needed to actively
transport the intestinal calcium through the calcium-ion canal in the gut epithelium (Bronner,
2003). Unfortunately, normal vitamin D level during lactation is lower than the gestation
stage (Kovacs & Kronenberg, 1997) therefore, the normal bone calcium deficit may not be
able to be compensated through calcium in feed, especially when the lactating cow is
expected to produce milk. It is also speculated that as the susceptible cows in the case farm
becoming pregnant for the second time, the elevation of serum Vitamin D in 2nd trimester
(Oliveri et al., 2004) on top of the surplus of calcium in the lactation ration may prepare the
bone for the subsequent normal negative net balance of bone calcium. Braithwaite (1983)
observed that the bone replenished the mineral deficit in the mid-lactation. In this study, the
speculation is supported by the finding of fewer cases (15%, 17/115) in the 2nd lactation and
none in the subsequent.
2.5.8 Plausible cause of spontaneous humeri fracture in dairy cattle
This study found that the selective calcium supplementation given to the lactation group
in the case farms may be responsible in suppressing the incident of spontaneous humeri
fractures in the second parity and higher. The similarity in the individual case attributes
which serve as distinctive features that associate spontaneous humeri fractures' syndrome
with the high calcium demand:
It occurred in late pregnancy or lactating stage.
It occurred mainly (87%, 93/106) within the first four-month post-partum.
The high quality indices (BW & PW) of the case animals suggesting that they had the
potential to produce more output (milk) as compared to the median of cows in New
Evidence from the other observations revealed that:
Mobilisation of bone mineral in late pregnancy and early lactation occurs in ewe
regardless the dietary calcium and phosphorus content (Braithwaite, 1983).
Prolonged lactation period increase the risk of lower bone density in female (Sowers
M & et al., 1993)
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Calcium deficit in gilt during the growing, continued to the lactation stage increase
the risk of spontaneous fracture in less than seven weeks of lactation (Spencer, 1979).
Pregnancy related transient demineralisation of bone during the 3rd trimester had been
reported in human (Curtiss & Kincaid, 1959).
Together with the age group and gender specificity, as well as the absence of other
classical syndromes that would relate the case animals to the popular believe of copper
deficiency such as lowered immunity, lower body weight, bowed leg, scour; we believe that
transient osteoporosis to pregnancy and lactation was the most likely causative agent of the
spontaneous humeri fractures in dairy cattle in New Zealand form 2007-2012.
2.5.9 Limitation
To our knowledge, this is the first study that comprehensively describes the
occurrences of spontaneous fracture of humeri bone in dairy cattle in New Zealand. While
bone fractures in ruminant have been widely reported (Gangl et al., 2006), the affected bones
were not specific. Case reports that specifically describe the occurrences of specific long
bone (femur) fractures in 10 years (Nichols 2010) only manage to gather 26 cases.
The study was purposive in nature; to investigate the incident of spontaneous humeri
fractures in dairy cattle. Hence, candidate farms were chosen based on the presence of the
outcome of interest. Recommendation from veterinarians, researchers and even farmers
whose farm had become or once were having the fracture syndrome, were obtained to earmark the possible candidate of the study. As the recommendations from the above-mentioned
personnel were pursued independently, the suggested farms overlapped. The final list of
farms which were believed to be affected by the fracture syndrome contained 30 farms,
which were contacted between December 2011 and January. Out of the 30 farms suggested,
only 73% (22/30) replied. This may potentially underestimate the actual count of cases under
study, but we believe; form the response of two farmers who wished not to be included in the
study, the remaining count was small. From 22 farms that returned the questionnaire, only
77% (115/149) cases reported in the questionnaire managed to be gathered, which may
introduce bias to the observation. Nevertheless, the study was the largest retrospective study
on spontaneous fracture in dairy population in New Zealand involving 115 cases in five
This study is categorised as a case series as it was lacking of control populations. Such
observational study was chosen as, to the best of our knowledge; the syndrome was relatively
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new. The only reference available for the spontaneous humeri fracture in dairy population
was the case report produced by Weston (2008). Even though in general, case series were
known to tender a low level of evidence (Wang & Attia, 2010), the contribution of the case
series cannot be denied. An example of a case series of an exceptionally rare pneumocystis
pneumonia among homosexual men in Southern California (Centers for Disease Control,
1981), contributed to the identification and recognition of the epidemic of the previously
unknown acquired immunodeficiency disease syndrome (AIDS)(Steinbrook, 2012).
2.6 Conclusion
The study managed to achieve the objective of describing the features of spontaneous
humeri fractures in New Zealand dairy population. The initial intuition that the spontaneous
fractures that involving a specific long bone were not random was concurred in the study;
there were observable patterns in the case animals and farms. This study is categorised as a
case-series as it was describing the case animals in five consecutive rearing seasons but
lacking of control population. As such, no conclusions were attempted on the cause of the
event except to provide some clues to the associated risk factors that constantly present in a
high proportion. The merit of the study was to alert the interested parties about the
similarities of the risk factors that were present prior or during the occurrence of the
spontaneous fracture in dairy cattle. A continuation of the study with other studies that able to
tender a higher level of evidence is highly recommended. This study prepared the information
regarding case properties, spatial and temporal factors as well as the herd properties of the
case group, which can be used for case-control studies. Based on the information gathered on
the case animals, it is hypothesized that the spontaneous humeri fracture syndrome that
affecting New Zealand dairy cow population from 2001-2012 was a transient osteoporosis to
pregnancy and lactation, as it was gender specifics and occurred during the period of
increased calcium demand. Similar events in swine and human heighten our suspicion on the
protagonist of transient osteoporosis in explaining the spontaneous fractures' syndrome dairy
cattle. Other risk factors that were consistently present with the case animals and/or case
farms, which may be associated with the fractures: lack of the dietary calcium in the growing
stages; breed of the dairy cows; high in the quality index (breeding and production worth);
increased in the walk speed of the lactating cows; involvement of a truck in the transportation
of heifers back from graziers.
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