Article

The relationship between transition period diseases and lameness, feeding time, and body condition during the dry period

Abstract and Figures

In this longitudinal study, we tested the hypothesis that cows that are lame around dry-off are at increased risk of transition diseases (TD), including metritis, subclinical ketosis (SCK), retained fetal membranes, hypocalcemia, or displaced abomasum. We also hypoth- esized that the relationship between lameness and TD would be mediated through reduced feeding time. We enrolled 461 cows at 9 wk before their expected calv- ing date on 6 commercial freestall farms in the lower Fraser Valley, British Columbia, Canada. Cows were gait-scored weekly using a scale of 1 to 5. Lameness status was classified based on consecutive gait scores as lame (2 consecutive gait scores = 3 or 1 score ≥4) or sound (2 consecutive gait scores ≤2). Lameness status was summarized as (1) lameness at dry-off (sound or lame); (2) lameness group (always sound = sound on all visits, chronically lame = lame on all visits, and other = changed from sound to lame or vice versa); and (3) proportion of weeks lame during the dry period. Body condition scores were recorded at dry-off and at calv- ing and collectively used to calculate change in body condition for each cow. A subsample of cows (n = 159) was evaluated for feeding time once a week during the dry period. All cows were evaluated for SCK (positive = β-hydroxybutyrate ≥1.2 mmol/L) and metritis (posi- tive = foul smell, red/brown watery vaginal discharge) every 3 to 4 d between d 3 and 17 after calving. We re- trieved data on treatment of retained fetal membranes, hypocalcemia, and displaced abomasum during the first 17 d after calving, cow parity, and milk produc- tion in the previous lactation from farm records. We created a binary variable, TD (any of SCK, metritis, retained fetal membranes, hypocalcemia, or displaced abomasum), to differentiate between healthy cows and cows that developed TD. Lameness at dry-off was asso- ciated with the occurrence of metritis and TD, but not with SCK. Cows that were chronically lame and cows that had an increased proportion of weeks lame during the dry period had higher occurrence of metritis and TD. Lameness was also associated with reduced feeding time, which in turn was associated with increased likeli- hood of SCK and TD, but not with metritis. Lame- ness was not associated with change in body condition; however, cows that lost body condition score during the dry period had increased odds of developing SCK, metritis, and TD. Change in body condition was highly associated with body condition score at dry-off. These results suggest that association between lameness and TD is partially mediated through reduced feeding time.
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ABSTRACT
In this longitudinal study, we tested the hypothesis
that cows that are lame around dry-off are at increased
risk of transition diseases (TD), including metritis,
subclinical ketosis (SCK), retained fetal membranes,
hypocalcemia, or displaced abomasum. We also hypoth-
esized that the relationship between lameness and TD
would be mediated through reduced feeding time. We
enrolled 461 cows at 9 wk before their expected calv-
ing date on 6 commercial freestall farms in the lower
Fraser Valley, British Columbia, Canada. Cows were
gait-scored weekly using a scale of 1 to 5. Lameness
status was classified based on consecutive gait scores as
lame (2 consecutive gait scores = 3 or 1 score ≥4) or
sound (2 consecutive gait scores ≤2). Lameness status
was summarized as (1) lameness at dry-off (sound or
lame); (2) lameness group (always sound = sound on all
visits, chronically lame = lame on all visits, and other
= changed from sound to lame or vice versa); and (3)
proportion of weeks lame during the dry period. Body
condition scores were recorded at dry-off and at calv-
ing and collectively used to calculate change in body
condition for each cow. A subsample of cows (n = 159)
was evaluated for feeding time once a week during the
dry period. All cows were evaluated for SCK (positive
= β-hydroxybutyrate ≥1.2 mmol/L) and metritis (posi-
tive = foul smell, red/brown watery vaginal discharge)
every 3 to 4 d between d 3 and 17 after calving. We re-
trieved data on treatment of retained fetal membranes,
hypocalcemia, and displaced abomasum during the
first 17 d after calving, cow parity, and milk produc-
tion in the previous lactation from farm records. We
created a binary variable, TD (any of SCK, metritis,
retained fetal membranes, hypocalcemia, or displaced
abomasum), to differentiate between healthy cows and
cows that developed TD. Lameness at dry-off was asso-
ciated with the occurrence of metritis and TD, but not
with SCK. Cows that were chronically lame and cows
that had an increased proportion of weeks lame during
the dry period had higher occurrence of metritis and
TD. Lameness was also associated with reduced feeding
time, which in turn was associated with increased likeli-
hood of SCK and TD, but not with metritis. Lame-
ness was not associated with change in body condition;
however, cows that lost body condition score during
the dry period had increased odds of developing SCK,
metritis, and TD. Change in body condition was highly
associated with body condition score at dry-off. These
results suggest that association between lameness and
TD is partially mediated through reduced feeding time.
Key words: feeding behavior, scan sampling, disease
incidence, risk factors
INTRODUCTION
During the transition period (i.e., ±3 wk of calving),
dairy cows are at the highest risk of developing infec-
tious and metabolic diseases (Ingvartsen, 2006; Mul-
ligan and Doherty, 2008; LeBlanc, 2010). Changes in
metabolism (Bell, 1995; Grummer, 1995) and decreased
DMI (Hayirli et al., 2002; Hayirli and Grummer, 2004)
in the weeks immediately before calving have been as-
sociated with the occurrence of 2 common transition
diseases (TD): metritis (Hammon et al., 2006; Huzzey
et al., 2007; Dubuc et al., 2010) and subclinical ketosis
(SCK; Goldhawk et al., 2009; Ospina et al., 2010).
Reduced DMI during the precalving period may pro-
long and aggravate negative energy balance during the
transition period (Grummer et al., 2004), resulting in
fat mobilization (Weber et al., 2013) that triggers a
cascade of proinflammatory processes in the adipose
tissue and the liver (Sordillo et al., 2009; Contreras
and Sordillo, 2011). Increased liver inflammation has
been linked to higher occurrence of TD (Bertoni et
al., 2008). This may explain the observed association
between body condition loss during the dry period and
the occurrence of uterine diseases (Chebel et al., 2018)
and SCK (Kaufman et al., 2016; Rathbun et al., 2017).
Although the etiologies of infectious and metabolic dis-
eases differ, it seems that DMI and body condition loss
The relationship between transition period diseases and lameness,
feeding time, and body condition during the dry period
Ruan R. Daros, Hanna K. Eriksson, Daniel M. Weary, and Marina A. G. von Keyserlingk*
Animal Welfare Program, Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
J. Dairy Sci. 103
https://doi.org/10.3168/jds.2019-16975
© 2020, The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Received May 16, 2019.
Accepted September 4, 2019.
*Corresponding author: nina@ mail .ubc .ca
Journal of Dairy Science Vol. 103 No. 1, 2020
underpin some of the mechanisms that contribute to
disease vulnerability.
Lameness has been studied in lactating cows, but
little is known about lameness during the dry period
and how it relates to TD. Lameness is a common
(Solano et al., 2015; Randall et al., 2019) and painful
condition (Whay et al., 2005; Chapinal et al., 2010)
that has been associated with reduced feeding time and
decreased DMI (Bach et al., 2007; Miguel-Pacheco et
al., 2014; Weigele et al., 2018). Based on these findings,
we propose that lameness during the dry period reduces
feed intake, resulting in negative energy balance and
greater body condition loss before calving, increasing
susceptibility to TD. A study by Calderon and Cook
(2011) supports this rationale: cows diagnosed as lame
during the 3 wk before calving had higher levels of
BHB (a marker for SCK; Duffield, 2000) after calving.
Although the association between lameness during the
close-up period and TD is to be expected (e.g., Vergara
et al., 2014), information is lacking on whether lame-
ness around dry-off also is also associated with TD.
The objectives of this study were to compare the
incidence of metritis and SCK between cows that were
lame or sound at dry-off, and to explore whether lame-
ness was associated with TD through changes in feed-
ing time and body condition loss during the dry period.
MATERIALS AND METHODS
This prospective longitudinal study was part of a
larger project designed to study lameness epidemiol-
ogy during the pre- and postpartum periods, and the
association between lameness and transition period
diseases. All participating dairy farms were located
in the lower Fraser Valley region in British Columbia,
Canada. Data were collected from May 2017 through
January 2018. The project was approved by the Animal
Care Committee at the University of British Columbia
(protocol A15–0084).
Sample Size Calculation
We hypothesized that disease incidence would be
higher for cows that were lame at dry-off compared
with cows that were sound. Based on previous reports
on the incidence of metritis (~20%; Chapinal et al.,
2011) we assumed a 10-point difference in incidence
between lame (20%) and sound (10%) cows. For SCK,
we assumed a 15-point difference (30% incidence for
lame cows vs. 15% incidence for sound cows), because
in previous studies the incidence of SCK ranged from
20 to 40% (LeBlanc, 2010; McArt et al., 2012). Us-
ing the sample size formula for testing differences in
proportions described by Dohoo et al. (2012), with a
power of 80% and an error rate of 5%, we estimated
a sample size of approximately 400 cows (200 in each
group, lame or sound) to detect a 10-point difference
in metritis cumulative incidence. For SCK, a sample
of 242 cows (121 in each group, lame or sound) would
be needed to detect a 15-point difference in SCK in-
cidence. We assumed that the effect of lameness on
disease incidence would be the same across farms, and
we did not account for data clustering, because all out-
comes and predictors of interests were measured at cow
level (Dohoo et al., 2012).
Farm and Cow Enrollment Criteria
Farms were pre-selected through a partnership with
a hoof-trimming company (AR-PE Hoof Trimming
Ltd., Abbotsford, BC, Canada); selection was based
on herd size (>160 lactating cows), freestall housing,
availability of individual cow records, and willingness
to participate in the study. From 9 enrolled farms, 6
were included in this study; on the remaining 3 farms,
data on TD was not collected.
On each farm, all parous cows with an expected calv-
ing date between July 21 and December 1, 2017, were
enrolled 9 wk before their expected calving. A total
of 461 cows were initially enrolled, of which 34 were
removed before calving. A detailed list of reasons for
cow removals is presented in Figure 1.
Farm Data Collection and Description
A structured interview was conducted with the farm
manager during the first visit to each farm. Key aspects
about the general herd management and health man-
agement of transition dairy cows were recorded. Infor-
mation about environmental variables, such as type of
flooring, number of stalls per pen, and number of feed
spaces per pen, was collected through environmental
inspection during the first visit. Number of cows in the
dry pens was recorded weekly to calculate stocking den-
sities at the feed bunk and the lying stalls. A detailed
description of the enrolled farms is presented in Table
1. Average herd size (mean ± standard deviation) was
361 ± 137 lactating cows, and milk production aver-
aged 11,866 ± 179 kg of milk per 305-d lactation.
Gait Scoring and Lameness Definition
Enrolled cows were gait-scored weekly using a
5-point scale described by Flower and Weary (2006).
The weekly gait scores were transformed into weekly
lameness status (lame or sound); lameness was defined
Daros et al.: LAMENESS AND TRANSITION DISEASES
Journal of Dairy Science Vol. 103 No. 1, 2020
as at least 2 consecutive gait scores of 3, or 1 gait score
≥4 (Eriksson et al., 2020). Cows were considered sound
when 2 consecutive gait scores were ≤2.
To test our primary objective, cows were retrospec-
tively classified as either sound or lame based on their
lameness status at the first week after enrollment (here-
after referred to as sound or lame at dry-off). To test
our secondary objective (to explore how lameness dur-
ing the dry period contributes to TD), we established
3 different lameness groups based on the proportion of
weeks the cows were lame during the precalving pe-
riod: chronically lame (cow remained lame during all
precalving visits), always sound (cow remained sound
during all precalving visits), and other (cow changed
lameness status during the dry period; lame to sound or
sound to lame). We also created a continuous variable:
number of weeks lame divided by total weeks assessed
during the dry period.
All gait scores were performed by 2 trained observers
(RRD, HKE). A detailed description of gait scoring
training and interobserver reliability is reported in
Eriksson et al. (2020). Live-scoring interobserver agree-
ment through weighted κ was 0.54 and 0.55 before and
after the study, respectively.
At each farm visit, all cows identified as severely lame
(gait score ≥4) were reported to farm personnel, but we
did not record whether these cases received treatment.
Body Condition Score and Body Condition Change
We recorded the BCS of enrolled cows on wk 8, 6, 4,
2, 1, and 0 before their expected calving date, using a
5-point scale in 0.5 points increments (Ferguson et al.,
1994). After calving, cows were assessed for BCS dur-
ing the first week postpartum, and again between wk
2 and 3 after calving. Because of differences between
expected and actual calving date, BCS was summarized
as the average BCS wk 8 to 10 before calving (hereafter
referred to as BCS at dry-off), and average BCS from
the week before calving to 2 d after calving (hereafter
referred to as BCS at calving). We chose to average
the BCS at dry-off and at calving to reduce the ef-
fect of inter-observer disagreements on the estimates of
change in body condition (ΔBC; Morin et al., 2017).
We further categorized BCS at dry-off and at calving
as thin (BCS <3.0), good (BCS 3.0–3.5), and fat (BCS
>3.5). We calculated ΔBC during the dry period as the
difference between BCS at calving and BCS at dry-off
(a positive value indicated that the cow increased her
BCS during the dry period). Seven cows did not have
data for BCS at dry-off; for these cows, we imputed
BCS at dry-off using the BCS assessed on wk 5 (n = 6)
and 4 (n = 1) before calving.
Four jointly trained observers assigned BCS. Interob-
server agreement was calculated with intra-class cor-
relation (ICC), which allows for the inclusion of more
than 2 non-random observers of ordinal data (Hallgren,
2012). The ICC was set for 2-way and agreement meth-
ods that considered the observer to not be chosen from
a random sample of observers, and that BCS scores
were in perfect agreement (i.e., penalized more if the
BCS were not exactly the same across observers; Hall-
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 1. Diagram of cows removed from the study, from top to
bottom. Top represents the beginning of the enrollment period (~wk 8
before calving), and the bottom represents the end of the study period
(~wk 2 after calving).
Journal of Dairy Science Vol. 103 No. 1, 2020
gren, 2012). Intra-class correlation coefficients take val-
ues from 0 (poor agreement) to 1 (excellent agreement);
the calculated ICC for the 4 observers was 0.81 [95%
confidence interval (CI): 0.73–0.87]. When evaluating
ICC the 4 observers independently scored 54 cows on
the same day in 1 of the participating farms. While
scoring the cows, observers did not share information
about the scores assigned. The minimum BCS assigned
among the observers was 2, and the maximum was 5.
Feeding Time
Time-lapse cameras (Digital 20 Megapixels Long
Range IR; Cuddeback, De Pere, WI) were installed to
record the feed bunk of the dry pens on 5 farms every
10 min. On the remaining farm, 3 cameras (CCTV
model WVCW504SP; Panasonic, Osaka, Japan) were
mounted 6 m above the feed bunk in the dry pens.
These cameras were connected to a digital video sur-
veillance system (GeoVision; GeoVision Inc., Corona,
CA), which recorded video continuously. Videos were
scan-sampled every 10 min to evaluate feeding time.
A 10-min scan-sampling protocol has been previously
validated for evaluating the feeding time of feedlot
cattle (Mitlöhner et al., 2001).
Enrolled cows were individually marked with alpha-
numeric symbols on their backs to facilitate recognition.
Coat color on the back (% of black), and face markings
were also recorded to facilitate recognition. Differences
in cow size on 1 farm made it impossible to determine
if small cows were present at the feed bunk. For that
reason, a random sample of focal cows (n = 159) was
selected from the other 5 farms after the on-farm data
collection was completed.
A focal cow was scored as present at the feed bunk
if the head was fully over the feed bunk (i.e., ears past
the feeding barrier). Daily feeding time in minutes was
derived by multiplying the number of images that the
focal animal was present during a 24-h period by 10.
Daily feeding time was recorded for each focal cow
Daros et al.: LAMENESS AND TRANSITION DISEASES
Table 1. Farm characteristics and management of the 6 participating freestall dairy farms in the lower Fraser Valley, British Columbia, Canada
Characteristic
Farm
A B C D E F
Herd size1 (no.) 185 510 540 310 330 290
Cows enrolled2 (no.) 15 105 101 79 73 54
Breed Holstein Holstein Holstein Holstein Mixed3Holstein
Milk production4 (kg/lactation) 12,718 12,819 12,942 10,461 9,134 12,210
Milkings per day (no.) 2 3 2 2 2 2
Feeding frequency (no.)
Dry cows 1 1 1 1 0.551
Lactating cows 1 1 1 2 1 2
Cows per feed space6 (no.)
Dry pens 0.8 0.9 1.0 0.8 1.2 0.8
Lactating pens 1.0 1.0 0.9 1.0 1.1 1.3
Cows per lying space7 (no.)
Dry pens 1.0 0.7 0.8 0.8 1.0 0.9
Lactating pens 1.0 0.8 0.9 1.0 1.1 1.0
Days dry (mean) 58 64 59 62 63 57
Pen changes from dry-off to 2 wk after calving (no.) 4 4 4 4 4 5
Pen layout
Far-off pens Freestall Freestall Freestall Freestall Freestall Freestall
Close-up pens Open pack Open pack Freestall Open pack Freestall Freestall
Pen flooring
Far-off pens Concrete Concrete Concrete Concrete Concrete
slats
Rubber
Close-up pens Sawdust,
concrete
Sawdust,
concrete
Concrete Sawdust,
concrete
Concrete
slats
Rubber
Manure handling Scraper Scraper Flush Tractor Robot Scraper
1Sum of dry and lactating animals; pregnant heifers not included.
2Number of enrolled cows that were not removed before calving.
3Holstein, Ayrshire, Jersey, and their crosses.
4Previous lactation (305-d corrected); based on data for all enrolled cows.
5Dry cows fed every other day.
6One feed space was defined as 1 head-lock. When no headlocks were present a feed space was considered 60 or 76 cm linear feed space for lactat-
ing and dry cows, respectively. Values represent the average number of cows per lying space during the study period.
7One lying space was defined as 1 freestall or 11 m2 in open-pack pens. Values represent the average number of cows per lying space during the
study period.
Journal of Dairy Science Vol. 103 No. 1, 2020
once per wk from wk 8 to 1 before calving. Because
of technical issues (e.g., drained camera batteries), or
because the cow was moved to another pen (e.g., to
the maternity or hospital pen), not all cows had weekly
measures of feeding time. On average, the focal cows
had feeding time data for 5.6 ± 1.5 d. A total of 8,337
images (from 23 focal cows from 4 farms) were evalu-
ated for the presence of focal cows by 5 trained observ-
ers. The same statistical method as described above for
BCS was applied. Calculated ICC for the 5 observers
was 0.96 (95% CI: 0.94–0.97).
Transition Period Diseases
Enrolled cows were examined for puerperal metritis
(hereafter referred to as metritis) and SCK every 3 to
4 d between d 3 and d 17 after calving, resulting in
4 assessments per animal. Metritis was scored 0 to 4
according to the consistency, smell and presence of pus
in cows’ vaginal discharge (clear = 0; <50% pus, no
fetid smell = 1; >50% pus, no fetid smell = 2; purulent
with foul smell = 3; red/brown watery fetid smell =
4). As defined by Sheldon et al. (2006), only cows with
a metritis score of 4 were considered to have metritis.
Subclinical ketosis was diagnosed with a cow-side blood
test (BHB ≥1.2 mmol/L; Duffield et al., 2009), using
handheld FreeStyle Precision Neo ketone monitoring
meters (Abbott Diabetes Care Ltd., Witney, UK; vali-
dated by Macmillan et al., 2017); blood was collected
from the cow’s tail vein. We did not assess cows for
clinical ketosis, but it is likely that some cows with high
levels of BHB were experiencing clinical ketosis. Infor-
mation about retained fetal membranes, and treatment
of hypocalcemia and displaced abomasum during the
first 17 DIM was retrieved from farm records. Cows
diagnosed with any disease during our health checks
were reported immediately to farm staff.
Data collected during the health checks were summa-
rized per cow; cows were considered positive for metritis
and SCK if they scored positive for these diseases on at
least 1 health check, whether they had another disease
or not. Cows that had fewer than 3 health checks and
were negative for metritis or SCK were assigned miss-
ing values for these diseases. Disease data were further
assigned binary categories: healthy, or developing a TD
(which included any 1 or a combination of SCK, metri-
tis, treatment of retained fetal membranes, treatment
of hypocalcemia, or treatment of displaced abomasum
during the first 17 DIM).
In addition to the health checks, 4 of 6 farms routine-
ly performed health assessments during the transition
period. These practices varied widely across farms. For
example, on 1 farm the farm manager conducted daily
assessments, but on another farm health checks were
conducted once every 2 wk by the herd veterinarian.
Disease treatment also varied widely, but most farms
reported using penicillin combined with other thera-
pies (4 of 6 farms) for the treatment of acute metritis.
Ketotic cows were treated with propylene glycol on 3
farms, and the remaining farms used oral drenches; in
the study region, it is common for oral drenches to
include propylene glycol in their formulation, but we
did not assess the formulation for the product used.
Retained fetal membranes was treated with penicillin
on 3 farms, with an intrauterine tetracycline flush on
1 farm, and on a case-by-case basis depending upon
veterinary advice on the remaining 2 farms.
Other Cow Variables
The animals were categorized as primiparous or mul-
tiparous based on their parity at dry-off. Because we
reported individual data from the pre- and postpartum
periods, when referring to data from the postpartum
period, parity is referred to as 2nd lactation (for the
primiparous at dry-off), and 3 or more lactations (for
the multiparous cows at dry-off). We retrieved indi-
vidual previous corrected 305-d milk yield in kilograms
from the last lactation and dry-off date from farm re-
cords. Previous milk yield was centered and scaled in
reference to the mean of the previous lactational milk
yield of all enrolled cows; the values used in analyses
represent the standard deviation from the mean.
Statistical Analyses
All statistical analyses were performed in R 3.5.2 (R
Core Team, 2019) using the RStudio interface (RStudio
Team, 2016). The list of statistical packages used, the
commented code and output, original data (in *.Rdata
and *.csv formats) and code scripts can be downloaded
at https: / / doi .org/ 10 .5683/ SP2/ UHWPX9.
All multilevel logistic regression models were fit-
ted through maximum likelihood using an adaptive
Gauss–Hermite quadrature method with 12 points to
better estimate model parameters (Pinheiro and Chao,
2006). The assumption of linearity between continuous
predictors and the log-odds of the outcome variables
were assessed graphically. All multilevel linear regres-
sion models were fitted through restricted maximum
likelihood. The normality and homoscedasticity of
lower level residuals were assessed through residual and
quantile-quantile plots.
In all models, we estimated confidence intervals
(set at 95%) of model parameters using the profile
likelihood method (Venzon and Moolgavkar, 1988).
Daros et al.: LAMENESS AND TRANSITION DISEASES
Journal of Dairy Science Vol. 103 No. 1, 2020
Multicollinearity was tested with a variation inflation
factor; no variables had a variation inflation factor >10
(Dohoo et al., 2012). Plausible biological interactions
were tested and kept in the model if P < 0.10. When
inclusion of interaction terms resulted in model conver-
gence failure, we explored the interaction in a separate
model (detailed below).
Hypothesis Testing. We tested the association
between lameness at dry-off (sound vs. lame) and the
occurrence of metritis, SCK, or TD, controlling for
known confounders (e.g., parity). For this, we built 3
multilevel logistic regression models with farm as ran-
dom intercept, 1 for each outcome variable: metritis,
SCK, and TD. In these models, we included parity,
previous lactation milk production, ΔBC, BCS at calv-
ing, and lameness at dry-off as predictors. In the model
for metritis, we also included retained fetal membranes
as a predictor. Based on our causal diagram (Figure 2),
ΔBC should be considered an intervening variable for
the association between lameness and TD, and there-
fore not be included in the models. However, in a pre-
liminary analysis we found that lameness (lameness at
dry-off, lameness group, or proportion of weeks lame)
was not associated with ΔBC, allowing us to include
ΔBC in the models. More details on which variables
were associated with ΔBC are presented below.
Exploratory Analyses. We also built models for
metritis, SCK, and TD similar to those described
above, but instead of using lameness at dry-off as pre-
dictors, we used lameness group as a predictor in one
set of models and proportion of weeks lame during the
dry period as predictor in another set of models. These
models allowed us to explore the associations between
chronic lameness and TD, and the cumulative effect
of lameness during the dry period on the incidence of
TD. In the models for SCK, the interaction between
lameness group and BCS at calving did not converge.
To remove the interaction term, we built separate mod-
els to measure the association between lameness and
SCK using a subset of data only from fat cows (calving
BCS >3.5). The rationale for this analysis was based
on the premise that lameness would contribute more to
SCK risk in fat cows than in cows with a lower body
condition, because low body condition seems to be a
protective factor for SCK (Duffield et al., 1998).
In our causal diagram (Figure 2), we proposed
that lameness reduces feeding time, and that reduced
feeding time (especially during the 3 wk before calv-
ing) increases the risk of developing TD. Hence, we
built models to test these different parts of the causal
diagram. To measure the association between weekly
lameness status and weekly feeding time, we built a
multilevel linear regression model, including the ran-
dom intercepts of farm and cow within farm, and using
week in relation to calving as the random slope. We
used feeding time (min/d) as the outcome variable,
and included lameness status (lame vs. sound), parity,
BCS at dry-off, previous lactation milk production, and
period (far-off = wk 8 to 4 before calving, and close-up
= wk 3 before calving to the week of calving) as predic-
tors. We included period as a predictor because feeding
time during the dry period changes at a different rates
in the far-off and close-up periods (Grummer et al.,
2004).
To assess the relationship between feeding time and
the occurrence of disease (metritis, SCK, and TD) we
built multilevel logistic regression models similar to
what has been described above; in these models, lame-
ness and ΔBC were considered intervening variables
and not included. Predictors for these models included:
feeding time (average per cow using the data available
for the 3 wk before calving), parity (primiparous vs.
multiparous), BCS at calving (thin, good, and fat), and
previous milk production. Cows’ BCS at calving did
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 2. Causal diagram showing the hypothesized causal web linking lameness to transition period disease. NEB = negative energy bal-
ance.
Journal of Dairy Science Vol. 103 No. 1, 2020
not converge because of the low number of thin cows in
the data set; BCS at calving was recoded as fat (BCS
>3.5) and not fat (BCS ≤3.5).
We also built a model to assess the factors associated
with ΔBC. Because ΔBC was a continuous variable
with no repeated measure (i.e., only 1 measure per cow)
we fitted 2 linear multilevel models using farm as a
random effect to: (1) measure the associations between
ΔBC and lameness group (always sound, chronically
lame, and other), parity, BCS at dry-off, previous milk
production, and number of days dry; and (2) measure
the association between ΔBC and feeding time, which
also included parity, BCS at dry-off, previous milk
production, and days dry. For this model, feeding time
was averaged per cow across the dry period. We found
a nonlinear association between feeding time and ΔBC
(https: / / doi .org/ 10 .5683/ SP2/ UHWPX9); to improve
model fit, we created a variable splitting feeding time
into 2 categories: low (average feeding time ≤4 h/d)
and high (average feeding time >4 h/d). To improve
model fit and test the difference in the slopes of feeding
time between low and high feeding time, the interaction
between continuous feeding time and categorical feed-
ing time was included in the model.
We extracted the residuals from a multilevel logistic
regression model that included farm as random effect;
the fixed effects of average feeding time in the close-
up period, parity, BCS at calving, ΔBC, and previous
lactation milk yield; and the response variable TD. To
test if lameness group (always sound, chronically lame,
or other) explained some of this residual variation in
TD, we fitted a univariable linear regression, using the
model residuals as the outcome and lameness group
as the predictor. This simple linear regression allowed
us to measure the model’s coefficient of determination
(R2), quantifying how much extra variation lameness is
explained.
RESULTS
The proportions of cows that were chronically lame,
always sound, or whose lameness status changed dur-
ing the dry period were 23, 33, and 43%, respectively.
Overall disease incidence and disease incidence per
lameness group are presented in Table 2. Cows spent
an average of 245 ± 53 min/d feeding. Feeding time in
relation to lameness status is presented on Figure 3.
Hypothesis Testing
Parameters estimates and confidence intervals for
factors associated with metritis, SCK, and TD are
presented in Table 3. Cows that were lame (vs. sound)
at dry-off had higher odds of metritis and TD post-
partum, but not of SCK. Cows in their third lactation
or later had higher odds of SCK and TD, but not of
metritis, compared with cows in their second lactation.
An increase in BCS from dry-off to calving was as-
sociated with reduced odds of metritis, SCK, and TD;
BCS at calving was associated only with the odds of
SCK. Thin cows (BCS < 3.0) and cows with good BCS
(3.0–3.5) at calving had lower odds of SCK than fat
cows (BCS > 3.5). Previous lactation milk production
was not associated with the odds of metritis, SCK, or
TD. Cows with retained fetal membranes after calving
had higher odds of metritis than cows that were not
diagnosed with retained fetal membranes.
Exploratory Data Analyses
Lameness and Metritis. Results from the models
evaluating lameness as a predictor for metritis occur-
rence are presented in Table 4. We found a tendency for
chronically lame cows to have higher odds of developing
metritis than cows that remained sound. This finding
Daros et al.: LAMENESS AND TRANSITION DISEASES
Table 2. Incidence of transition period diseases in the first 3 wk after calving by lameness group in 427 dairy
cows from 6 dairy farms in the lower Fraser Valley, British Columbia, Canada
Disease
Overall
incidence (%)
Incidence per lameness group (%)
Always sound Chronically lame Other1
Subclinical ketosis235 31 41 35
Metritis328 21 39 28
Retained fetal membranes410 10 11 9
Hypocalcemia45 4 8 4
Displaced abomasum43 0 4 3
Transition disease554 46 66 54
1Cows whose lameness status changed during the dry period.
2Positive if blood BHB ≥1.2 mmol/L on at least 1 health check.
3Positive if vaginal discharge was red/brown, watery, and had a fetid smell on at least 1 health check.
4As per farm records.
5Any of the above.
Journal of Dairy Science Vol. 103 No. 1, 2020
was supported by the linear relation between the pro-
portion of weeks lame and the odds of metritis; for
each 10% increase in weeks lame, the odds of metritis
increased by 1.07 times. Cows that gained BCS from
dry-off to calving had reduced odds of metritis. Body
condition score at calving, parity, and previous lacta-
tion milk production were not associated with the odds
of metritis. Retained fetal membranes were associated
with increased odds of metritis. No interactions were
retained in any of the models for metritis.
Lameness and SCK. Results from the models
evaluating lameness during the dry period as a pre-
dictor for SCK are presented in Table 5. Neither the
proportion of weeks lame during the dry period nor
chronic lameness during the dry period was associated
with higher odds of SCK. Gaining BCS during the
dry period was associated with reduced odds of SCK,
regardless of BCS at calving. Cows that were thin at
calving had reduced odds of SCK compared with cows
that were fat. Animals in their third lactation or later
had higher odds of having SCK than cows in their sec-
ond lactation.
When considering only fat cows at calving (n = 108),
chronically lame cows tended to have higher odds of
SCK [odds ratio (OR) 3.44; 95% CI: 1.00 to 13.36; P =
0.06] compared with cows that remained sound. In this
model, neither ΔBC (OR 0.57; 95% CI: 0.18 to 1.83;
P = 0.34), parity (OR 2.17; 95% CI: 0.75 to 6.63; P =
0.16), nor previous milk production (OR 0.69; 95% CI:
0.43 to 1.08; P = 0.11) was associated with the odds
of SCK.
Lameness and TD. Results from the models evalu-
ating lameness during the dry period as a predictor for
TD are presented in Table 6. Chronically lame cows
had higher odds of TD compared with animals that re-
mained sound. For each 10% increase in the proportion
of weeks lame, the odds of TD increased by 1.09 times.
Cows with 3 or more lactations had increased odds of
TD compared with cows in their second lactation, and
cows that gained BCS during the dry period had re-
duced odds of TD. Body condition score at calving and
previous lactation milk production were not associated
with the odds of TD. No interactions were retained in
any of the models for TD.
Lameness and Feeding Time. Lameness was as-
sociated with reduced feeding time; when lame cows
spent on average 20 min/d (95% CI: −30 to −10 min/d;
P < 0.01) less time feeding than when sound (Figure
3). Also, multiparous cows spent less time feeding (−19
min/d; 95% CI: −36 to −3 min/d; P = 0.02) than
primiparous cows. Compared with fat cows, cows with
good BCS and those with thin BCS spent 33 min/d
(95% CI: 16 to 49 min/d; P < 0.01) and 35 min/d
(95% CI: 6 to 63 min/d; P < 0.01) more time feeding,
respectively. Previous lactation milk production was
not associated with time spent feeding (6 min/d; 95%
CI: −1 to 13 min/d; P = 0.09) during the dry period.
We found an interaction (see Figure 3) between week
in relation to calving and period (far-off and close-up).
During the close-up period, feeding time decreased at a
greater rate (−19 min/wk; 95% CI: −27 to −10 min/
wk; P < 0.01) than during the far-off period (−1.7
min/wk; 95% CI: −7.9 to 3.6 min/wk; P = 0.55). We
found no interaction between lameness status, week to
calving and period.
Feeding Time and TD. Average feeding time dur-
ing the close-up period (OR 0.8; 95% CI: 0.5 to 1.1; P
= 0.20), parity (third lactation or later; OR 0.8; 95%
CI: 0.3 to 2.0; P = 0.64), BCS (≤3.5; OR 1.0; 95%
CI: 0.4 to 2.8; P = 0.98) and previous lactation milk
production (OR 0.9; 95% CI: 0.6 to 1.4; P = 0.73) were
not associated with metritis.
For each 1 h increase in average feeding time during
the close-up period, the odds of SCK decreased by 0.7
times (95% CI: 0.4 to 0.9; P = 0.02); cows in their third
lactation or later had higher odds of SCK (OR 4.2; 95%
CI: 1.7 to 12.2; P < 0.01) than cows in their second
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 3. Estimated time spent feeding in relation to week before
calving by lameness status of 159 dry cows from 5 commercial freestall
dairy farms in the lower Fraser Valley, British Columbia, Canada.
Each dot represents the estimated feeding time of each cow observed
each week. Dots were jittered using the geom_jitter function, and lines
are estimated using the loess method from the geom_smooth function
(ggplot2 package; Wickham, 2016). When lame, cows spent an average
of 20 min/d (95% CI: −30 to −10 min/d; P < 0.01) less time feeding
than when sound.
Journal of Dairy Science Vol. 103 No. 1, 2020
Daros et al.: LAMENESS AND TRANSITION DISEASES
Table 3. Parameters from the models for the association between lameness at dry-off and the occurrence of metritis, subclinical ketosis, and
transition disease in the first 3 wk after calving in 403 dairy cows from 6 dairy farms in the lower Fraser Valley, British Columbia, Canada
Predictor
Metritis1
Subclinical ketosis2
Transition disease3
Odds ratio
(95% CI) P-value
Odds ratio
(95% CI) P-value
Odds ratio
(95% CI) P-value
Lameness at dry-off
Sound Referent Referent Referent
Lame 1.9 (1.12–3.11) 0.02 1.13 (0.70–1.83) 0.62 1.82 (1.15–2.92) 0.01
Parity
Second lactation Referent Referent Referent
Third or greater lactation 0.86 (0.49–1.51) 0.60 2.58 (1.53–4.42) <0.01 1.81 (1.11–2.97) 0.02
ΔBC40.46 (0.23–0.90) 0.02 0.36 (0.19–0.68) <0.01 0.47 (0.26–0.86) 0.01
BCS at calving
>3.5 Referent Referent Referent
3.0–3.5 1.15 (0.65–2.07) 0.64 0.67 (0.40–1.12) 0.13 0.67 (0.40–1.12) 0.13
<3.0 1.10 (0.24–4.75) 0.90 0.07 (0.00–0.44) <0.01 0.39 (0.11–1.36) 0.13
Previous lactation milk yield51.17 (0.88–1.58) 0.28 0.83 (0.63–1.09) 0.18 0.91 (0.70–1.19) 0.50
Retained fetal membranes6
No Referent
Yes 9.70 (4.42–22.58) <0.01
Random intercept
Farm Variance: 0.38 Variance: 0.35 Variance: 0.29
1Positive if vaginal discharge was red/brown, watery, and had a fetid smell on at least 1 health check.
2Positive if blood BHB ≥1.2 mmol/L on at least 1 health check.
3Any of the following: subclinical ketosis, metritis, retained fetal membranes, hypocalcemia, displaced abomasum.
4Change in BCS from dry-off to calving; a 1-unit change indicates that a cow gained 1 BCS point over the dry period.
5Scaled variable: a 1-unit change equals a change of 1 standard deviation from the mean previous lactation milk production from all enrolled
cows.
6Retained fetal membranes was not included as predictor in the models for subclinical ketosis or transition disease. Data for retained fetal mem-
branes were collected from farm records.
Table 4. Parameters from the models evaluating lameness as a predictor for metritis in 403 dairy cows from 6 dairy farms in the lower Fraser
Valley, British Columbia, Canada
Predictor
Lameness group
Proportion of weeks lame
Odds ratio (95% CI) P-value Odds ratio (95% CI) P-value
Lameness group
Always sound Referent
Chronically lame 1.85 (0.91–3.75) 0.09
Other11.50 (0.83–2.73) 0.18
Proportion of weeks lame 1.002 (1.00–1.01) 0.05
Parity
Second lactation Referent Referent
Third or greater lactation 0.84 (0.48–1.49) 0.56 0.83 (0.47–1.48) 0.53
ΔBC30.47 (0.24–0.92) 0.03 0.47 (0.24–0.94) 0.03
BCS at calving
>3.5 Referent Referent
3.0–3.5 1.15 (0.65–2.08) 0.64 1.14 (0.64–2.06) 0.66
<3.0 1.02 (0.22–4.46) 0.98 1.05 (0.23–4.60) 0.95
Previous lactation milk yield41.17 (0.87–1.57) 0.29 1.17 (0.87–1.57) 0.29
Retained fetal membranes
No Referent Referent
Yes 10.43 (4.74–24.46) <0.01 10.16 (4.63–23.67) <0.01
Random intercept
Farm Variance: 0.41 Variance: 0.41
1Cows whose lameness status changed during the dry period.
2Adjusted odds for each 10% increase in weeks lame during the dry period = 1.07.
3Change in BCS from dry-off to calving; a 1-unit change indicates that a cow gained 1 BCS point over the dry period.
4Scaled variable: a 1-unit change equals a change of 1 standard deviation from the mean previous lactation milk production from all enrolled
cows.
Journal of Dairy Science Vol. 103 No. 1, 2020
lactation. Body condition score at calving (≤3.5; OR
0.9; 95% CI: 0.4 to 2.1; P = 0.76) and previous milk
production (OR 0.8; 95% CI: 0.5 to 1.1; P = 0.23) were
not associated with the odds of SCK.
A 1 h increase in average feeding time during the
close-up period also reduced the odds of TD by 0.7
times (95% CI: 0.5 to 1.0; P = 0.05). Third lactation
or higher (OR 1.5; 95% CI: 0.7 to 3.4; P = 0.30), BCS
Daros et al.: LAMENESS AND TRANSITION DISEASES
Table 6. Parameters from the models evaluating lameness as a predictor for transition disease1 in 404 dairy cows from 6 dairy farms in the lower
Fraser Valley, British Columbia, Canada
Predictor
Lameness group
Proportion of weeks lame
Odds ratio (95% CI) P-value Odds ratio (95% CI) P-value
Lameness group
Always sound Referent
Chronically lame 2.22 (1.19–4.22) 0.01
Other21.48 (0.90–2.44) 0.12
Proportion of weeks lame 1.013 (1.00–1.01) <0.01
Parity
Second lactation Referent Referent
Third or greater lactation 1.73 (1.06–2.86) 0.03 1.70 (1.04–2.81) 0.04
ΔBC40.49 (0.27–0.88) 0.02 0.49 (0.27–0.88) 0.02
BCS at calving
>3.5 Referent Referent
3.0–3.5 0.67 (0.39–1.12) 0.12 0.66 (0.39–1.10) 0.11
<3.0 0.35 (0.10–1.23) 0.10 0.37 (0.10–1.37) 0.12
Previous lactation milk yield50.91 (0.69–1.18) 0.48 0.91 (0.69–1.18) 0.48
Random intercept
Farm Variance: 0.38 Variance: 0.32
1Any of the following: subclinical ketosis, metritis, retained fetal membranes, hypocalcemia, or displaced abomasum within 3 wk of calving.
2Cows whose lameness status changed during the dry period.
3Adjusted odds for each 10% increase in weeks lame during the dry period = 1.09.
4Change in BCS from dry-off to calving; a 1-unit change indicates that a cow gained 1 BCS point over the dry period.
5Scaled variable: a 1-unit change equals a change of 1 standard deviation from the mean previous lactation milk production from all enrolled
cows.
Table 5. Parameters from the models evaluating lameness as a predictor for subclinical ketosis1 in 404 dairy cows from 6 dairy farms in the
lower Fraser Valley, British Columbia, Canada
Predictor
Lameness group
Proportion of weeks lame
Odds ratio (95% CI) P-value Odds ratio (95% CI) P-value
Lameness group
Always sound Referent
Chronically lame 1.62 (0.84–3.15) 0.15
Other21.28 (0.75–2.20) 0.38
Proportion of weeks lame 1.003 (1.00–1.01) 0.13
Parity
Second lactation Referent Referent
Third or greater lactation 2.39 (1.40–4.13) <0.01 2.37 (1.39–4.10) <0.01
ΔBC40.37 (0.19–0.68) <0.01 0.37 (0.19–0.68) <0.01
BCS at calving
>3.5 Referent Referent
3.0–3.5 0.65 (0.39–1.09) 0.10 0.64 (0.38–1.08) 0.10
<3.0 0.06 (0.00–0.41) 0.01 0.06 (0.00–0.42) <0.01
Previous lactation milk yield50.84 (0.63–1.10) 0.20 0.84 (0.63–0.10) 0.20
Random intercept
Farm Variance: 0.38 Variance: 0.39
1Positive if blood BHB ≥1.2 mmol/L on at least 1 health check.
2Cows whose lameness status changed during the dry period.
3Adjusted odds for each 10% increase in weeks lame during the dry period = 1.05.
4Change in BCS from dry-off to calving; a 1-unit change indicates that a cow gained 1 BCS point over the dry period.
5Scaled variable: a 1-unit change equals a change of 1 standard deviation from the mean previous lactation milk production from all enrolled
cows.
Journal of Dairy Science Vol. 103 No. 1, 2020
(≤3.5; OR 0.6; 95% CI: 0.3 to 1.4; P = 0.24), and previ-
ous lactation milk production (OR 0.9; 95% CI: 0.6 to
1.2; P = 0.45) were not associated with changes in odds
of TD. The trends of feeding time during the dry period
by TD are presented on Figure 4.
Lameness and TD After Controlling for Co-
variates. When modeling the residuals from the multi-
level logistic regression on TD, lameness group (always
sound, chronically lame, and other) further explained
residual variance (model statistics: F = 3.14; 2 and 151
df; P = 0.05; adjusted R2 = 0.03).
Factors Associated with ΔBC. We found no clear
association between lameness group and ΔBC (see Fig-
ure 5). Compared with cows that remained sound dur-
ing the dry period, the ΔBC for chronically lame cows
and cows that changed lameness status was −0.7 BCS
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 4. Descriptive data for feeding time during the dry period by transition disease category, based on the assessment of 159 dry cows
from 5 commercial freestall dairy farms in the lower Fraser Valley, British Columbia, Canada. Each dot represents the measured feeding time
of each cow observed each week. Dots were jittered using the geom_jitter function, and lines are estimated using the loess method from the
geom_smooth function (ggplot2 package; Wickham, 2016). Gray dots and lines represent data from cows that were not diagnosed with disease.
Red dots and lines represent data from cows that were diagnosed with disease. Transition disease included one or a combination of subclinical
ketosis, metritis, retained fetal membranes, hypocalcemia, and displaced abomasum recorded within 3 wk after calving.
Journal of Dairy Science Vol. 103 No. 1, 2020
points (95% CI: −0.17 to 0.02; P = 0.12) and −0.7 BCS
points (95% CI: −0.15 to 0.01; P = 0.08), respectively.
Cows that were thin and cows that had good BCS at
dry-off gained BCS (0.7, 95% CI: 0.5 to 0.8, P < 0.01;
and 0.4, 95% CI: 0.3 to 0.4, P < 0.01, respectively)
during the dry period compared with cows that were
fat at dry-off; see Figure 5. For each day dry, cows in-
creased their BCS 0.003 points (95% CI: 0.001 to 0.006;
P < 0.01). Parity (multiparous 0.1; 95% CI: −0.6 to
0.09 BCS points; P = 0.76) and previous lactation milk
production (−0.007; 95% CI: −0.05 to 0.03; P = 0.75)
were not associated with ΔBC.
On the model using the subsample of cows (n = 159)
assessed for feeding time, feeding time was positively
associated with ΔBC when average feeding time was
≤4 h/d: an extra hour of feeding was associated with
a 0.2-point increase in ΔBC (95% CI: 0.01 to 0.4; P
= 0.05; see Figure 6), but for average feeding time >4
h/d, we found no relationship between feeding time
and ΔBC (−0.08 points; 95% CI: −0.7 to 0.7; P =
0.22; see Figure 6). Similarly, as described above, in
the subsample of cows, cows that were thin and cows
with good BCS at dry-off gained BCS (0.8 points, 95%
CI: 0.6 to 1.1, P < 0.01; and 0.4 points, 95% CI: 0.2
to 0.4, P < 0.01, respectively) through the dry period
compared with fat cows. Number of days dry (0.003;
95% CI: −0.00 to 0.01; P = 0.11), parity (multiparous
−0.06; 95% CI: −0.2 to 0.1; P = 0.35), and previous
lactation milk production (0.02; 95% CI: −0.05 to 0.08;
P = 0.52) were not associated with ΔBC.
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 5. Boxplot showing body condition change during the dry period in relation to BCS at dry-off and lameness group. Data are from
426 dry cows from 6 commercial freestall dairy farms in the lower Fraser Valley, British Columbia, Canada. Each dot represents the measured
BCS for each cow. Body condition score was categorized as fat (>3.5), good (3.0 to 3.5), and thin (<3.0). The lameness category “other” in-
cluded cows whose lameness status changed during the dry period. Lameness group was not associated with body condition change during the
dry period. Body condition score at dry-off was associated with body condition change; fat cows lost BCS during the dry period, and thin and
good BCS cows gained BCS.
Journal of Dairy Science Vol. 103 No. 1, 2020
DISCUSSION
Our results support the hypothesis that lameness
during the dry period is associated with TD. Lame-
ness identified 2 mo before calving was associated with
increased risk of TD, highlighting the importance of
screening cows for lameness around dry-off.
We partially explored the causal mechanism through
which lameness relates to transition health as proposed
by Calderon and Cook (2011); namely, that lameness
reduces feeding time and consequently DMI. In a study
similar to ours, researchers from Germany also found
that cows decreased their feeding time when they be-
came lame (Grimm et al., 2019), albeit with a magni-
tude 3 times greater (−65 min/d when lame) than in
our study (−19 min/d when lame). The differences in
feeding time between their study and ours may be due
to reporting differences (their study reported only raw
values rather than predicted values), breed difference
(Simmental cows vs. Holstein cows) and differences in
lactational stages (lactating vs. nonlactating cows). A
cross-sectional study by González et al. (2008) reported
a reduction of 19 min/d in average feeding time of
lame cows compared with non-lame cows. However,
they included only severe lameness cases, whereas we
included milder cases of lameness. Another study com-
paring non-lame with moderately lame cows also found
that lame animals had reduced feeding time, but no
effect size was reported (Weigele et al., 2018). Together,
these studies highlight that lameness is associated with
reduced feeding time, suggesting that lame cows also
have lower DMI (Bach et al., 2007). Although reduced
feeding time does not always result in lower DMI (e.g.,
Grimm et al., 2019), some studies have shown that
increased feeding time and increased DMI are corre-
lated (e.g., Johnston and DeVries, 2018). Given that we
were not able to measure DMI and that most previous
studies conducted on commercial farms considered only
lactating cows, further research on this behavior in dry
cows is warranted.
Reduced feeding time during the weeks before calv-
ing was associated with SCK and TD, but not metritis.
The lack of association between feeding time and me-
tritis contradicts previous findings (Urton et al., 2005;
Huzzey et al., 2007). Recently, Neave et al. (2018)
conducted a study in the same experimental farm as
the one used for the previous studies of Urton et al.
(2005) and Huzzey et al. (2007), and also failed to cor-
roborate their findings. Neave et al. (2018) argued that
the differences in findings could be due to the fact that
Huzzey et al. (2007) did not screen for SCK, which
could have confounded the results because SCK has
been associated with changes in feeding activity (Gold-
hawk et al., 2009). To explore the hypothesis proposed
by Neave et al. (2018), we included (data not shown)
SCK as a predictor in the metritis and feeding time
model, and we were unable to detect any association
between feeding time and metritis incidence, even when
controlling for SCK. Huzzey et al. (2007) did not report
if cows were diagnosed for lameness, and Neave et al.
(2018) included only sound cows in their analysis. We
did not include lameness as a predictor in our model for
metritis and feeding time because feeding time would
have become an intervening variable in the association
between lameness and metritis. However, our results
showing that lame cows spent less time feeding may
partially explain the discrepancy between the results
reported by Neave et al. (2018) and Huzzey et al.
(2007), given that Huzzey et al. (2007) did not screen
cows for lameness. Regarding SCK, our results were in
line with those reported by Goldhawk et al., (2009),
who reported that cows feeding less before calving were
more likely to develop SCK. Neave et al. (2018) did not
find differences in feeding time during the precalving
period for cows with both SCK and metritis compared
with healthy cows. Although we did not specifically
combine SCK and metritis, cows with a TD spent less
time feeding during the dry period.
Uterine diseases and SCK have been associated with
BCS loss during the dry period (Kaufman et al., 2016;
Daros et al.: LAMENESS AND TRANSITION DISEASES
Figure 6. Interaction plot showing estimated body condition
change during the dry period depending on average time spent eating
during the dry period for 159 dry cows from 5 commercial freestall
dairy farms in the lower Fraser Valley, British Columbia, Canada.
Each dot represents the estimated body condition change (y-axis)
along the average time spent feeding per day (x-axis). Lines represent
the linear relationship between the variables, splitting average feeding
time into 2 categories: high (red) and low (blue).
Journal of Dairy Science Vol. 103 No. 1, 2020
Chebel et al., 2018), which in turn is associated with
BCS around dry-off (Chebel et al., 2018). In addition
to corroborating previous findings that changes in BCS
are associated with BCS at dry-off (Hoedemaker et al.,
2009; Chebel et al., 2018), we were able to evaluate the
association between lameness and body condition loss
during the dry period; surprisingly, lameness was not as-
sociated with body condition loss. Some have suggested
that cows naturally change BCS through homeorhetic
mechanisms (Bauman and Currie, 1980; Roche et al.,
2009), which, we speculate, may have had more influ-
ence on body condition changes than lameness. Based
on our findings and those ones described by Chebel et
al. (2018), it seems that monitoring BCS throughout
lactation with the goal of achieving moderate BCS at
dry-off may be beneficial for transition health. This
strategy has been tested in grazing cows by comparing
cows that had their BCS experimentally manipulated
to achieve moderate BCS at dry-off to cows that had
slightly higher BCS at dry-off; the animals with lower
BCS had better metabolic (Roche et al., 2015) and
immune status (Crookenden et al., 2017) during the
transition period.
Independent of ΔBC, lameness during the dry period
was associated with TD. Chronically lame cows tended
to be more likely to develop metritis, and we found an
association between proportion of weeks lame during
the dry period and metritis development. We found a
similar result for TD. These results explain our findings
that lameness around dry-off is associated with metritis
and TD, because cows that were lame around dry-off
often continued to be lame during the dry period. Using
only 1 lameness assessment within the 3 wk before calv-
ing, Vergara et al. (2014) reported an increased likeli-
hood for severely lame, but not moderately lame, cows
to be treated for TD in the post-calving period. The use
of cross-sectional data to categorize cows as moderately
lame may result in a high proportion of false positives
Eriksson et al. (2020), biasing the estimates toward the
null (Dohoo et al., 2012) and perhaps explaining the
lack of association for moderate lameness reported by
Vergara et al. (2014).
Lameness was not independently associated with
SCK. Similarly, Kaufman et al. (2016) did not retain
lameness in their final model exploring risk factors for
SCK. This was not unexpected, given that thin cows
have a lower likelihood of SCK (Vanholder et al., 2015)
and are likely to experience repeated cases of lameness
(Randall et al., 2015). For this reason, we explored the
interplay between lameness and BCS at calving on the
occurrence of SCK. From a separate analysis of the
subgroup of cows that were fat at calving, our results
suggest that fat cows that are also chronically lame
during the dry period have an increased likelihood of
developing SCK postpartum compared with sound fat
cows. Further studies on SCK and lameness should ac-
count for this relationship by exploring the interaction
between BCS and lameness status.
We evaluated the additive effects of body condition
loss during the dry period and BCS at calving on metri-
tis, SCK, and TD. We found that both ΔBC and BCS
at calving were independently associated with likelihood
of SCK. Cows that are overconditioned around calving
have a higher risk of SCK (e.g., Vanholder et al., 2015).
Although Kaufman et al. (2016) also reported an effect
of ΔBC on the likelihood of SCK, they limited their
measures of change in BCS from 3 weeks before calving
to 2 weeks after calving, which meant that changes in
BCS may have been a consequence of SCK.
Change in body condition was associated with the
likelihood of cows developing metritis and TD, a simi-
lar finding to that of Chebel et al. (2018), who found
an association between body condition loss during the
dry period and increased likelihood of uterine diseases.
Previous studies have described low BCS at calving as
a risk factor for uterine disease (Duffield et al., 2009;
Dubuc et al., 2010). In our study, low BCS at calving
was not associated with metritis or TD. We speculate
that the higher risk for cows with low BCS to develop
uterine diseases after calving reported previously (Duff-
ield et al., 2009; Dubuc et al., 2010) may have been
due to an association between excessive body condition
loss during the dry period and low body condition at
calving (Chebel et al., 2018).
Chronic lameness during the dry period explained
some of the variation in the likelihood of TD even after
controlling for ΔBC, average feeding time during the
close-up period, parity, milk production, and BCS at
calving. This finding provides some evidence that lame-
ness may be related to TD through a different pathway
than feeding time. Given that lame cows have a higher
level of inflammation (Tadich et al., 2013), this could
lead to an increased susceptibility to TD (see review by
Bradford et al., 2015). Studies on haptoglobin levels (a
marker for inflammation) in prepartum sound and lame
cows may provide additional insights on the interplay
between lameness and transition period diseases.
CONCLUSIONS
Lameness at dry-off was associated with increased
odds of metritis and TD. These results were further
supported by our exploratory analyses, showing that
chronic lameness during the dry period was associated
with higher odds of TD. One of the mechanisms through
which lameness may be associated with TD is through
decreased feeding time; throughout the dry period,
lame cows spent less time feeding than sound cows, and
Daros et al.: LAMENESS AND TRANSITION DISEASES
Journal of Dairy Science Vol. 103 No. 1, 2020
lower feeding time was in turn associated with higher
odds of TD. Independent of lameness, body condition
loss during the dry period was also associated with
increased odds of transition period diseases. Moreover,
body condition loss was associated with BCS at dry-off;
cows that were fat at dry-off lost body condition, and
thin cows gained body condition during the dry period.
These results suggest that reducing lameness during
the dry period and avoiding overconditioning at dry-off
may improve transition health.
ACKNOWLEDGMENTS
We thank Samantha Jung, Paige Macdonald, and
Wali Sahar (Animal Welfare Program) for their help
during data collection, the participating farmers for
their time and allowing us to conduct this project on
their properties, the hoof trimmers at AR-PE Hoof
Trimming Ltd. (Abbotsford, BC, Canada), and Mar-
tin Stigge (Vancouver, BC, Canada) for helping with
software development and R code support. During this
project RRD was supported by the Science Without
Borders Program (CNPq – National Council for Scien-
tific and Technological Development, Brazil) and HKE
was supported by Tetra-Laval through the Sweden-
America Foundation (Stockholm, Sweden). Funding for
this project has been provided by the British Columbia
Dairy Association through the Dairy Industry Research
and Education Committee, and the Agriculture and
Agri-Food Canada and the British Columbia Ministry
of Agriculture through the Canada–British Columbia
Agri-Innovation Program under Growing Forward 2, a
federal-provincial-territorial initiative. The program is
delivered by the Investment Agriculture Foundation of
British Columbia. Opinions expressed in this document
are those of the author and not necessarily those of the
Governments of Canada and British Columbia or the
Investment Agriculture Foundation of British Colum-
bia. The Governments of Canada and British Columbia,
and the Investment Agriculture Foundation of British
Columbia, and their directors, agents, employees, or
contractors will not be liable for any claims, damages,
or losses of any kind whatsoever arising out of the use
of, or reliance upon, this information. General funding
for the Animal Welfare Program is provided by the
Canada’s Natural Sciences and Engineering Research
Council Industrial Research Chair Program (Ottawa,
ON, Canada) with contributions from Dairy Farmers of
Canada (Ottawa, ON, Canada), the British Columbia
Dairy Association (Burnaby, BC, Canada), Westgen
Endowment Fund (Milner, BC, Canada), Intervet
Canada Corporation (Kirkland, QC, Canada), Zoetis
(Kirkland, QC, Canada), Novus International Inc.
(Oakville, ON, Canada), the British Columbia Cattle
Industry Development Fund (Kamloops, BC, Canada),
Alberta Milk (Edmonton, AB, Canada), Valacta (St
Anne-de-Bellevue, QC, Canada) and CanWest DHI
(Guelph, ON, Canada).
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ORCIDS
Ruan R. Daros https: / / orcid .org/ 0000 -0003 -2331 -1648
Marina A. G. von Keyserlingk https: / / orcid .org/ 0000 -0002 -1427
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Daros et al.: LAMENESS AND TRANSITION DISEASES
... Our data corroborated this, presenting differences between month -1 and month +1, even if our data includes healthy as well as less healthy cows. Others reported such transition patterns as useful parameters to relate to transition diseases [50][51][52]. ...
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... Feeding time did not differ between DD affected heifers and those without DD lesions however there was a tendency for feeding time to change over time. These results were surprising since we hypothesised that heifers with DD would have spent less time feeding knowing that feeding time is decreased in dairy cattle with health disorders (González et al., 2008;Huxley, 2013;Daros et al., 2020). Additionally, we expected to observe a difference in feeding time since we observed a difference in rumination time and rumination is known to be correlated to feeding time (Schirmann et al., 2012). ...
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... This evaluation was carried out when cows were walking along a straight, flat, hard surface, either on the way from the prepartum paddocks to the chute or in the pens near the milking parlor. Prepartum cows with score ≥ 4 were excluded since severe lameness has been shown to affect the cow's behavior, the metabolic status, and it is associated with infectious diseases (Calderon and Cook, 2011;Daros et al., 2020). Additionally, days to calving, dry period length (days), and close-up period length (days) of each cow was recorded in the farms' software and retrieved at the end of the study period; from this information, tables for individual farms were created in Microsoft Access 2003 (Microsoft Corp.). ...
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... The finding corroborates previous reports suggesting an increased risk of lameness during early lactation (Green et al., 2014;Foditsch et al., 2016). Lameness is amongst the diseases that develop during the transition period and influenced by events such as negative energy balance, immunosuppression, and depletion in body reserve (Novotna et al., 2019;Daros et al., 2020). ...
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Identification of the associations of cow feeding behavior with productivity is important for supporting recommendations of strategies that optimize milk yield and composition. The objective of this study was to identify associations between measures of feeding behavior and milk production using data collated from studies of the feeding behavior of lactating dairy cows. A database containing behavior and production data for 132 dairy cow-week observations (mean of 7 d of consecutive data per cow) was assembled from 5 studies. Cows averaged (mean ± standard deviation) 1.8 ± 0.9 lactations, 108.4 ± 42.7 d in milk, and 654.6 ± 71.4 kg of body weight during each observation week. Production data included dry matter intake (27.0 ± 3.1 kg/d), milk yield (43.0 ± 7.0 kg/d), milk fat content (3.60 ± 0.49%), and milk protein content (3.05 ± 0.25%). Behavioral data included feeding time (230.4 ± 35.5 min/d), feeding rate (0.13 ± 0.03 kg/min), meal frequency (9.0 ± 2.0 meals/d), meal size (3.2 ± 0.9 kg/meal), daily mealtime (279.6 ± 51.7 min/d), and rumination time (516.0 ± 90.7 min/d). Data were analyzed in multivariable mixed-effect regression models to identify which behavioral variables, when accounting for other cow-level factors (days in milk, parity, and body weight) and dietary characteristics (forage level, nutrient content, and particle distribution), were associated with measures of production. Dry matter intake was associated with feeding time (+0.02 kg/min) and tended to be associated with rumination time (+0.003 kg/min) and meal frequency (+0.2 kg/meal). Similarly, milk yield was associated with feeding time (+0.03 kg/min) and rumination time (+0.02 kg/min), and tended to be associated with meal frequency (+0.3 kg/meal). Milk fat yield was associated with meal frequency (+0.02 kg/meal). Overall, our results suggest that milk yield and component production may be improved in situations where cows are able to increase their time spent feeding, in more frequent meals, and time spent ruminating.
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The objective of this study was to evaluate the use of a cow-side device (FreeStyle Precision Neo™) to diagnose ketosis and hypoglycemia based on measures of blood β-hydroxybutyrate (BHBA) and glucose. Eleven commercial dairy farms were visited and blood samples were taken from Holstein cows between 2 and 14 days in milk, yielding 441 samples for BHBA analysis and 308 samples for glucose analysis. Concentrations of BHBA and glucose were measured in two ways, 1) using the cow-side device with whole blood immediately after sampling and 2) serum samples analyzed with a standard laboratory assay (Animal Health Laboratory, University of Guelph, Canada). The accuracy of the device was determined by comparing the results to the laboratory method as well as the ability to diagnose ketosis (BHBA ≥ 1.2 mmol/L) and hypoglycemia (glucose < 2.5 mmol/L). The concordance correlation coefficient (CCC), Bland-Altman plot and Kappa coefficient were calculated to evaluate agreement between the 2 methods using SAS (version 9.3). The CCC was 0.92 for BHBA and 0.56 for glucose measurements. The 95% confidence intervals of the Bland-Altman plot encompassed 97% and 95% of the mean difference between methods for BHBA and glucose measurements, respectively. The Kappa coefficients were 0.78 for BHBA and 0.23 for glucose measurements. These results indicate that the cow-side device is accurate for rapid measurement of blood BHBA and diagnosis of ketosis on farms but is not accurate for measurement of blood glucose concentrations and diagnosis of hypoglycemia.
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Extensive efforts have been made to identify more feed-efficient dairy cows, yet it is unclear how selection for feed efficiency will influence metabolic health. The objectives of this research were to determine the relationships between residual feed intake (RFI), a measure of feed efficiency, body condition score (BCS) change, and hyperketonemia (HYK) incidence. Blood and milk samples were collected twice weekly from cows 5 to 18 d postcalving for a total of 4 samples. Hyperketonemia was diagnosed at a blood β-hydroxybutyrate (BHB) ≥1.2 mmol/L and cows were treated upon diagnosis. Dry period, calving, and final blood sampling BCS was recorded. Prior mid-lactation production, body weight, body weight change, and dry matter intake (DMI) data were used to determine RFI phenotype, calculated as the difference between observed DMI and predicted DMI. The maximum BHB concentration (BHBmax) for each cow was used to group cows into HYK or not hyperketonemic. Lactation number, BCS, and RFI data were analyzed with linear and quadratic orthogonal contrasts. Of the 570 cows sampled, 19.7% were diagnosed with HYK. The first positive HYK test occurred at 9 ± 0.9 d postpartum and the average BHB concentration at the first positive HYK test was 1.53 ± 0.14 mmol/L. In the first 30 d postpartum, HYK-positive cows had increased milk yield and fat concentration, decreased milk protein concentration, and decreased somatic cell count. Cows with a dry BCS ≥4.0, or that lost 1 or more BCS unit across the transition to lactation period, had greater BHBmax than cows with lower BCS. Prior-lactation RFI did not alter BHBmax. Avoiding over conditioning of dry cows and subsequent excessive fat mobilization during the transition period may decrease HYK incidence; however, RFI during a prior lactation does not appear to be associated with HYK onset.
Article
Body condition score (BCS) is strongly correlated with energy reserves. The ease, rapidity of scoring, and high intra- and inter-observer repeatability make it a widely used herd management tool in bovine practice and in scientific studies. Loss or gain of BCS, rather than a single BCS measurement, is frequently used to monitor energy balance in dairy cows. It is unknown if the difference between 2 BCS measures taken at different moments (ΔBCS) would demonstrate inter-observer agreement similar to that of a single BCS measurement. The objective of this study was to compare inter-observer agreement of BCS and ΔBCS in dairy cows when multiple observers perform data collection. An observational study was conducted between April and September 2015; 3 observers independently assessed BCS of 73 Holstein cows from 1 commercial dairy herd. Body condition score assessments of the animals were performed between 1 and 20 d in milk (early lactation; exam 1) and again between 41 and 60 d in milk (peak of milk production; exam 2). Quadratic weighted kappa (κw) was computed to quantify agreement between observers for single BCS measurements and ΔBCS. For single BCS measurements, κw of 0.79 (95% CI: 0.69, 0.85) and 0.84 (95% CI: 0.77, 0.89) were obtained for exam 1 and exam 2, respectively. Such values would be interpreted as strong agreement and are consistent with the available literature on BCS repeatability. When computing agreement for ΔBCS, a κw value of 0.49 (95% CI: 0.32, 0.63) was obtained, suggesting moderate agreement between observers. These findings suggest that studies investigating single BCS measures could use many observers with a high degree of accuracy in the results. When ΔBCS is the parameter of interest, more reliable results would be obtained if one observer conducts all assessments.