Alveolar-Membrane Diffusing Capacity Limits
Performance in Boston Marathon Qualifiers
Kaleen M. Lavin1, Allison M. Straub1, Kathleen A. Uhranowsky1, James M. Smoliga3,
Gerald S. Zavorsky1,2*
1 Human Physiology Laboratory, Marywood University, Scranton, Pennsylvania, United States of America, 2 The Commonwealth Medical College, Scranton, Pennsylvania,
United States of America, 3 Department of Physical Therapy, High Point University, High Point, North Carolina, United States of America
Abstract
Purpose: (1) to examine the relation between pulmonary diffusing capacity and marathon finishing time, and (2), to
evaluate the accuracy of pulmonary diffusing capacity for nitric oxide (DLNO) in predicting marathon finishing time relative
to that of pulmonary diffusing capacity for carbon monoxide (DLCO).
Methods: 28 runners [18 males, age = 37 (SD 9) years, body mass = 70 (13) kg, height = 173 (9) cm, percent body fat = 17 (7)
%] completed a test battery consisting of measurement of DLNO and DLCO at rest, and a graded exercise test to determine
running economy and aerobic capacity prior to the 2011 Steamtown Marathon (Scranton, PA). One to three weeks later, all
runners completed the marathon (range: 2:22:38 to 4:48:55). Linear regressions determined the relation between finishing
time and a variety of anthropometric characteristics, resting lung function variables, and exercise parameters.
Results: In runners meeting Boston Marathon qualification standards, 74% of the variance in marathon finishing time was
accounted for by differences in DLNO relative to body surface area (BSA) (SEE = 11.8 min, p,0.01); however, the relation
between DLNO or DLCO to finishing time was non-significant in the non-qualifiers (p = 0.14 to 0.46). Whereas both DLCO
and DLNO were predictive of finishing time for all finishers, DLNO showed a stronger relation (r2 = 0.30, SEE = 33.4 min,
p,0.01) compared to DLCO when considering BSA.
Conclusion: DLNO is a performance-limiting factor in only Boston qualifiers. This suggests that alveolar-capillary membrane
conductance is a limitation to performance in faster marathoners. Additionally, DLNO/BSA predicts marathon finishing time
and aerobic capacity more accurately than DLCO.
Citation: Lavin KM, Straub AM, Uhranowsky KA, Smoliga JM, Zavorsky GS (2012) Alveolar-Membrane Diffusing Capacity Limits Performance in Boston Marathon
Qualifiers. PLoS ONE 7(9): e44513. doi:10.1371/journal.pone.0044513
Editor: Mauricio Rojas, University of Pittsburgh, United States of America
Received March 30, 2012; Accepted August 3, 2012; Published September 11, 2012
Copyright:  2012 Lavin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no funding or support to report.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: zavorsky@marywood.edu
Introduction
In 2010, nearly one half million runners in the United States
completed a marathon, representing about 0.2% of the U.S.
population over 18 years of age. Many marathoners aspire to
qualify for the Boston Marathon, participation in which is
restricted to a relatively small percentage of runners by age and
gender-graded qualification standards. In 2011, approximately
40,000 runners qualified for the 2012 or 2013 Boston Marathon,
representing about 10% of all runners who finished a marathon in
the United States. These statistics are readily available to the
public online at MarathonGuide.com.
Due to its aura and relative popularity, marathon running has
been examined in several scientific studies, with particular
attention given to the metabolic [1] and physiological [2,3,4,5,6]
correlates of running a fast marathon. Although these correlates
are multifactorial and widely debated [7], it is well established that
aerobic capacity ( _VO2max) is an important determinant of
marathon performance. Approximately 40 to 77% of the variance
in marathon performance is attributable to _VO2max [5,8,9,10,11].
In addition to aerobic capacity, marathon-specific endurance is
related to performance, such that the ability to sustain a higher
percentage of _VO2max is correlated with a faster marathon [12].
On average, top marathoners (,136 minutes for men, ,158
minutes for women) run at 85 to 90% _VO2max [5], while those in
the 156 to 240 minute range run at approximately 75 to 85% of
_VO2max [10,13].
Aerobic capacity is dependent on the integrated function of
major organ systems, including the heart, lung, and skeletal muscle
[14]. Unlike the heart and skeletal muscle, the lung does not
readily adapt to endurance training [15,16], possibly limiting
_VO2max [15]. Even in those who are highly aerobically fit, heavy
exercise may cause arterial oxygen pressure to drop #80 mm Hg,
while the alveolar-to-arterial oxygen pressure difference may
increase to $25 mmHg [17]. In this way, arterial oxyhemoglobin
saturation is reduced, leading to a decrease in
_VO2max and,
subsequently, endurance performance [18,19,20].
Recently, alveolar-membrane diffusing capacity (measured at
rest) has been shown to be very closely related to _VO2max in fit and
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obese individuals [21,22] and to longevity in heart disease patients
[23]. Specifically, when measured at rest, pulmonary diffusing
capacity for nitric oxide (DLNO, mL NO.min21.mmHg21) – a
surrogate for alveolar-membrane diffusing capacity for carbon
monoxide (DmCO) [24,25] – has been shown to be related to
aerobic capacity in fit men and women, such that for every 1 unit
increase in DLNO, _VO2max increases by 0.3 mL O2. kg21. min21
[21]. The ratio of DLNO to DmCO is debated. It has been said
that DmCO = DLNO 4 2.42, or, more recently, DmCO =
DLNO 4 2.06 to 2.26. As long as the ratio is kept consistent
within a study, any percent change in DmCO or pulmonary
capillary blood volume is still valid. Furthermore, alveolar
membrane conductance is the main pulmonary diffusing capacity
component representative of fitness, with the exception of
pulmonary capillary blood volume (VC) and the blood transfer
conductance (H) for CO (HCO). There are mixed data as to
whether DLCO or DLNO is a more valid predictor of aerobic
capacity, but overall diffusion capacity does appear to be
significantly correlated with aerobic capacity in fit subjects
[21,22]. Nitric oxide (NO) has been shown to bind more strongly
than CO to hemoglobin [26], leading to a higher value for
membrane conductance and a diffusion measurement more
reflective of total membrane diffusion. An additional benefit of
measuring DLNO simultaneously with DLCO is a reduction in
time and effort of the procedure.
As there is a relation between DLNO and
_VO2max, and
between _VO2max and marathon running performance, it follows
that DLNO may be related to marathon performance, such that
pulmonary diffusing capacity introduces a limitation that influ-
ences marathon performance. However, it is likely that this
correlation may be observed in only well-trained marathoners,
who are more likely to experience pulmonary limitations to oxygen
availability. Pulmonary limitations have been observed in elite
athletes, and as many as 50% of highly-trained individuals
experience low oxygen concentrations in the blood (hypoxemia),
potentially due to diffusion limitation [27]. Whereas hypoxemia is
most frequently observed at exercise intensities near maximal
exertion, it is possible that endurance events such as a marathon
place constraints on the working lung muscles regardless of the
submaximal speed at which most runners compete. Indeed,
Amann et al. [28] found that pulmonary limitations were capable
of significantly decreasing performance in a 5 kilometer cycling
time trial. This effect is likely intensified during a marathon,
which, although run at a slower pace, is more than eight times as
long. Another study shows that seasoned runners experience
significant decreases in diffusing capacity following completion of a
marathon [29], suggesting an important role for the lungs in an
event that requires submaximal speed but maximal overall effort.
Based on these observations, the purpose of this study was to
compare the relation between DLNO and DLCO (indexed to
body surface area, BSA) and marathon running performance. It
was hypothesized that pulmonary diffusion limitation would exist
in faster runners, defined herein as those meeting qualification
standards for the Boston Marathon (Boston Qualifiers, BQ).
Qualification for this prestigious event is dependent on one’s
performance relative to age and gender standards, thus eliminating
the concerns associated with grouping subjects based on marathon
time alone (e.g. creating a younger or predominantly male group).
Furthermore, the Steamtown Marathon is a certified qualification
course and frequently qualifies over 20% of its participants for the
Boston event. This local event therefore provides the opportunity
to study differences between sub-elite and more recreational
marathoners using a less ambiguous distinction than running pace.
In analyzing these data, the relation between marathon
finishing time and DLNO or DLCO in both groups was examined
using a linear regression model. No significant relation between
these factors was expected in non-qualifiers (non-BQ), whereas
qualifiers (BQ) were expected to show a significant correlation
between finishing time and DLNO/DLCO. Additionally, it was
hypothesized that DLNO would show a stronger relation with
marathon finishing time than would DLCO, in agreement with
previous findings [21,30].
Methods
Twenty-eight endurance trained subjects (18 males, 10 females),
reported for preliminary testing 2 to 3 weeks before the 2011
Steamtown Marathon in Scranton, PA. Institutional Review
Board-approved informed written consent and a Physical Activity
Readiness Questionnaire were obtained from all subjects before
participation. Anthropometrics (body mass, height, BSA) and age
were obtained, and percent body fat (BF %) was measured using
Dual Energy X-ray Absorptiometry (DEXA) (Lunar ProdigyTM,
GE Medical Systems, Madison, WI).
Pulmonary function tests, consisting of spirometry maneuvers to
identify
obstructive
or
restrictive
patterns,
were
conducted
according to established guidelines [31]. The maneuver to
determine DLNO and DLCO was also performed according to
established guidelines [32], with a 5 to 6 second breath-hold [21].
Because this one-step maneuver allows simultaneous measurement
of DLNO and DLCO, pulmonary capillary blood volume (VC)
was then calculated as follows: DmCO was computed as DLNO 4
2.42. The 1/HCO was determined from Roughton and Forster
[33] as (0.73+0.058 ? PAO2) ? (14.6/[Hb]), where alveolar oxygen
pressure (PAO2) was 100 mmHg, and the hemoglobin concentra-
tion [Hb] was set as 14.6 g. dL21 for males, and 13.4 g. dL21 for
females [32]. As such, 1/HCO was 1.310 for males and 1.427 for
females. VC was then obtained by solving for it using the following
equation [33]:
1
DLCO ~
1
DmCO z
1
HCO:Vc
Reference equations were then used to compare each marathon
runner’s lung function to normative data from the standard
population [34,35].
After the lung function tests were completed, running economy
testing was performed on treadmill at a 2% grade to simulate
outdoor running conditions at three different sub-maximal
running speeds, each lasting 5 minutes. The treadmill was
calibrated before the first subject was tested. Throughout testing,
heart rate (HR) was measured using a Polar heart rate monitor
(Model S610, Polar Electro USA, Lake Success, NY). Metabolic
data were collected using breath-by-breath analysis (Sensormedics
Vmax 229D, Viasys, CA).
Assuming that steady state exercise had been achieved within
the first three minutes, means for metabolic data for the last two
minutes of each stage were computed. Running economy for each
stage was computed as the _VO2 required to travel one kilometer
and expressed as mL O2.min21.km21. Mean running economy for
the three speeds was then computed to serve as a measure of
overall running economy.
The final stage of the running economy test protocol was
followed immediately by a graded exercise test, in which treadmill
speed was increased by 0.5 mph every minute until volitional
exhaustion. Several cardiorespiratory parameters, including max-
imum respiratory exchange ratio (RERmax), maximum heart rate
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(HRmax), maximum expired ventilation ( _VEmax), and
_VO2max
were measured, and the treadmill speed at which _VO2max was
obtained was recorded (v _VO2max). If this speed was sustainable for
less than a full minute, the highest speed sustained for 60 seconds
was also recorded. Marathon-specific endurance (%V _VO2max) was
calculated by dividing the runner’s mean speed for the Steamtown
marathon by v _VO2max, with higher values indicating performance
at a greater relative physiologic intensity. Since _VO2 could not be
directly measured during the race, average _VO2 for the marathon
was calculated from the slope of the regression line between speed
and _VO2 for each subject, using the three speeds of the running
economy test. Average speed for the marathon was then entered
into each subject’s own equation to solve for oxygen consumption.
Univariate ANCOVAs or independent t-tests (with a confidence
interval of 95%) were used to determine whether differences in
finishing time, _VO2max (both absolute, in L.min21, and relative, in
mL.kg21.min21), and lung function parameters existed between
BQ and non-BQ groups. Age and gender served as covariates for
the
ANCOVA.
Step-wise
multiple
linear
regressions
were
conducted to determine variables most closely related to finishing
time for the entire sample, as well as for each group separately.
DLNO and DLCO normalized to body surface area (BSA) were
included in regression analyses to account for the effects of body
mass and height on lung size. Other predictor variables entered
into regression analysis include gender, age, body mass, body fat
percentage,
_VO2max (L O2. min21), running economy (mL
O2. kg21. km21), DLNO, DLCO, and marathon specific endur-
ance. To address the significance of diffusing capacity, the relation
between DLNO or DLCO and finishing time was further explored
in a bivariate regression analysis for both BQ and non-BQ groups.
The data were analyzed by SPSS Version 19.0, (SPSS Inc.,
Chicago, IL). Statistical significance was declared when p,0.05.
Results
A total of 392 Steamtown Marathon finishers (22% of marathon
participants) met qualification standards for the 2012 or 2013
Boston Marathon. Of the 28 subjects in this study, 10 runners (6
males, 4 females) (36%) qualified for Boston. Anthropometric
measurements (Table 1) indicated that significant differences exist
between BQ’s and non-BQ’s with respect to age and body fat
percentage (p,0.05).
The graded exercise test to volitional exhaustion lasted 10.1(1.2)
minutes including the final 5-min running economy bout. The
_VO2max in L O2. min21 from that test was not different between
groups; however, relative
_VO2max (mL O2. kg21. min21) was
significantly different between the two groups (p,0.01) such that
BQ’s had a mean (standard deviation)
_VO2max about 11(2.5)
mL O2. kg21. min21 greater than that of non-BQ’s. There was a
non-significant trend (p = 0.08) for body mass to differ between
groups. During the graded exercise test, BQ’s attained a maximal
treadmill speed 20% faster than non-qualifiers (p,0.05). Addi-
tionally, BQ’s completed the marathon at a higher percentage of
v _VO2max (7565%) than did non-BQ’s (6764%, p,0.001). For
both groups combined, there was a significant bivariate relation
between _VO2max (mL O2. kg21. min21) and marathon finishing
time (adjusted r2 = 0.47, SEE = 37.5 min, p,0.05).
Percent of predicted values for a lung function tests were not
significantly different between groups (Table 2). Three subjects in
each group had a DLNO greater than the upper limit of normal
(ULN). Two BQ’s had a DLCO above the ULN, while 5 non-
BQ’s had a DLCO that surpassed the ULN. Chi-square analysis
reveals that there is not a significant difference in the proportion of
subjects with an abnormally high diffusion capacity (DLCO or
DLNO) between groups (data not included).
Mean finishing time for all subjects was 220.0 minutes,
(range = 142.6 to 288.9). Weight loss from the marathon was
comparable between the two groups [1.0 (1.4) kg for BQ’s; 0.9
(0.8) kg for non-BQ’s, p = 0.746]. Ten of the twenty-eight
participants (6 males, 4 females) qualified for the Boston Marathon
(average
time = 180.0+23.1 min);
the
average
time
for
the
remaining 18 (12 males, 6 females) was 242.2+28.3 minutes.
Finishing time was significantly faster in BQ’s when controlling for
age and gender (p,0.01). Step-wise linear regression determined
that finishing time for all subjects was dependent on maximum
treadmill
speed
and
specific
endurance
(adjusted
r2 = 0.97,
SEE = 6.9 minutes p,0.05); however, 80% of the variance in
finishing time is accounted for by differences in maximum
treadmill
speed
sustained
for
60
seconds
alone
(adjusted
r2 = 0.80, SEE = 17.7 minutes, p,0.05).
In BQ’s, the strongest relation identified was between finishing
time and DLNO normalized to BSA. For non-BQ’s, finishing time
was best predicted by maximum treadmill velocity sustained for 60
seconds and specific endurance, where 74% of the variance in
finishing time is accounted for by differences in maximum
treadmill velocity. The relation between DLNO normalized to
BSA and finishing time was not significant for non-BQ’s
(p = 0.127). A significant difference was found between the
correlation coefficients of the two linear regressions (two-tailed
z = 22.15, p = 0.03). When regression lines of DLNO normalized
to BSA versus finishing time plotted on the same axes, the
regressions intersect at a point corresponding to a finishing time of
178.1 minutes (Figure 1), suggesting that the relation between
DLNO normalized to BSA and marathon time begins to change
around 237 m. min21 pace (6 minutes, 47 seconds per mile).
DLCO normalized to BSA was also correlated to finishing time in
BQ subjects, to a lesser extent. For non-BQ, no significant relation
between the variables is evident (p = 0.46). These regressions
intersect at the point corresponding to 184.3 minutes (Figure 2).
Discussion
The novelty of this study lies in that it shows that the relation
between pulmonary factors (measured at rest) and marathon
performance may differ between athletes of different skill level. In
particular, this study was able to isolate an approximate time point
at which the relation between pulmonary diffusing capacity for
nitric oxide and marathon finishing time changes for trained
endurance athletes, pinpointing a pace at which lung function
becomes limiting to performance. Whereas runners qualifying for
the Boston Marathon, because of their overall faster pace, are
limited by DLNO, non-qualifiers probably experience a more
mechanical limitation, such as leg turnover (related to maximum
treadmill velocity).
The primary purpose of this study was to compare the
correlation of DLNO and DLCO to marathon running perfor-
mance. The results demonstrate that there was a significant slope
(indicating a strong correlation) between DLNO and DLCO
(normalized to BSA) versus marathon finishing time only in
runners that qualified for the Boston Marathon, with these
variables showing a stronger predictive relation to finishing time
than either _VO2max or running economy. DLNO was shown to be
the
strongest
predictor
of finishing
time,
such
that
every
1 mL. min21. mmHg21.m22 increase in DLNO at rest projects
that finishing time will decrease by about 1.4 minutes (with a range
of 0.8 to 2.1 min). These results strongly suggest that alveolar-
capillary membrane conductance may be performance-limiting in
DLNO Predicts Marathon Finishing Time
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runners that complete a marathon in 3 hours or faster, as shown
by the intersection of regression lines for BQ and non-BQ groups
(Figure 1 and 2). These figures also demonstrate that DLNO
relative to BSA is a more accurate predictor of finishing time than
DLCO, as the former correlation shows a larger adjusted r2 and a
lower standard error of the estimate.
The
physiological
mechanism
closely
relating
DLNO
to
marathon performance in BQ’s is speculative, given that these
subjects ran at approximately 75% of _VO2max, a value consistent
elsewhere in those with similar running abilities [10,13]. Though
arterial oxygen pressure and the alveolar-to-arterial oxygen
pressure difference was not measured throughout the race in this
study, others have shown hypoxemia is not induced in fit athletes
running half of a full marathon at ,75%
_VO2max [36].
Nonetheless, we suggest that, in well-trained runners, there is a
_VO2 threshold at which pulmonary diffusion limits oxygen
consumption. In other words, these individuals run the marathon
at a speed at which _VO2 is high enough that gas diffusion at the
alveolar-capillary membrane becomes a physiological bottleneck,
and those with greater alveolar-capillary membrane conductance
are able to maintain greater arterial oxygen saturation. Similarly,
non-BQ’s likely complete the marathon at a
_VO2 at which
pulmonary diffusion is not limiting; this may explain the lack of
relation between DLNO and performance in this group. Thus,
individuals
who
have
superior
alveolar-capillary
membrane
conductance (high DLNO measurements), and yet do not reach
a ‘‘heart’’ or ‘‘muscle limitation,’’ (i.e., non-BQ’s) would not have
Table 1. Anthropometric Data for Boston Qualifiers and non-Qualifiers.
BQ (n = 10)
Non-BQ (n = 18)
Total (n = 28)
ANTHROPOMETRICS
Age (yr)*
33 (9)
40 (7)
37 (9)
22–50
29–52
22–52
Weight (kg)
64.1 (11.1)
73.2(13.3)
69.9 (13.2)
42.2–84.5
45.0–103.0
42.2–103.0
Height (cm)
170.7 (9.0)
174.0 (9.2)
172.8 (9.1)
154.0–186.7
156.0–187.0
154.0–187.0
Body Fat (%)*
13.1 (7.12)
19.1 (6.7)
17.0 (7.3)
5.1–24.1
9.0–34.5
5.1–34.5
CARDIOPULMONARY VARIABLES AT MAXIMAL EXERCISE
_VO2max (L/min)
3.75 (0.64)
3.56 (0.64)
3.63 (0.64)
2.71–4.75
2.25–4.52
2.25–4.75
_VO2max (mL/kg/min)*
59.4 (8.3)
48.7 (5.0)
52.5 (8.1)
49.1–73.1
38.3–60.4
38.3–73.1
RERmax
1.17 (0.07)
1.16 (0.06)
1.16 (0.06)
1.06–1.30
1.06–1.28
1.06–1.30
VEmax (L/min)
119.91 (21.10)
112.03 (18.46)
114.85 (19.43)
82.6–141.13
81.00–149.30
81.00–149.30
HRmax (bpm)
187 (12)
178 (12)
181 (12)
169–202
152–198
152–202
RUNNING PERFORMANCE
Running Economy (mL/kg/km){
194.5 (13.0)
205.8 (19.1)
202.0 (18.1)
180.8–224.5
172.9–247.6
172.9–247.6
Running Economy (mL/kg/min)
43.2 (5.9)
36.3 (3.7)
38.8 (5.6)
36.0–52.0
30.0–44.2
30.0–52.0
Maximum Treadmill Speed for 60 seconds (m/min)*
316 (34)
266 (31)
284 (40)
271–362
228–316
228–362
Marathon Finishing Time (min)
180.0 (23.1)
242.2 (28.3)
220.0 (40.0)
142.0–203.0
200.4–289.0
142.0–289.0
% _VO2max for Marathon
76.4 (6.9)
74.8 (7.2)
75.3 (7.0)
63.0–82.4
63.0–88.3
63.0–88.3
Specific Endurance (% _V VO2max)*
75.31 (5.44)
66.47 (3.97)
69.62 (6.20)
63.16–81.72
56.26–72.04
56.26–81.72
Data are reported as mean (SD) values and range.
*denotes significant difference (p,0.05) between BQ and non-BQ subjects. Controlling for age and gender using an ANCOVA did not affect the outcome of statistical
analyses.
{Running Economy calculated at average speed for group; BQ = 222.2 (30.0) m/min, non-BQ = 177.2 (20.4) m/min.
doi:10.1371/journal.pone.0044513.t001
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any performance advantage over other individuals who have lower
alveolar-capillary membrane conductance. In fact, studies have
demonstrated that marathon running causes a significant drop in
pulmonary diffusing capacity [29,37]. About 30% of the drop in
DLNO (normalized to BSA) post-exercise is accounted for by
marathon finishing time (p = 0.046) [29]. Thus, for every 1 minute
improvement
in
marathon
time,
DLNO
is
reduced
by
1.2 mL.min21.mmHg21.m22 [29]. The diminished DLNO with
marathon running can be expected, since _VO2max accounts for
about 40 to 77% of the variance in marathon performance
[5,8,9,10,11] and about 40% of the change in DLNO from pre- to
post-exercise [38]. Therefore, it is possible that individuals with
larger alveolar-capillary membrane conductance at the start of the
marathon have a physiological advantage: diffusion impairments
that may arise during the race will likely not decrease diffusion
capacity to problematic levels.
Only one other study to date has examined the association
between pulmonary diffusion and marathon finishing time using
both DLNO and DLCO as predictors [29]. While Manier and
colleagues did not intend to examine this association, the data set
was available in the publication. In BQ runners (n = 9, mean
finishing time = 177.0615.0 min), the relation between DLNO
indexed to BSA and finishing time was present, but it was
not as strong as in the current study (adjusted r2 = 0.30,
SEE = 12.5 min,
p = 0.073).
In
Manier’s
study,
for
every
1 mL.min21.mmHg21.m22 increase in DLNO at rest, marathon
finishing time was 0.8 minutes faster (ranging from 1.8 minutes
faster to 0.1 minute slower) [29]. Combining these data with those
from the present study suggests that 30 to 74% of the variance in
DLNO (mL. min21. mmHg21.m22) at rest is related to marathon
finishing time in BQ’s, while no such relation exists in non-BQ’s.
Additionally, controlling for age and gender does not affect this
correlation in either study separately or collectively [29]. Combin-
ing the data from these independent studies further supports that
pulmonary diffusing capacity is an important contributor to
marathon performance in well-trained runners. It is also important
to note that while the BQ group represents a well-trained
population and some of the subjects in this study performed at a
very high level, international class runners tend to have even higher
values of _VO2max and, possibly, an even greater dependence on
alveolar-capillary membrane conductance.
Although DLNO normalized to BSA was only related to
finishing time in BQ’s, DLNO did not significantly differ between
BQ and non-BQ whether indexed to BSA (p = 0.078) or not
(p = 0.80). DLNO is usually higher in fit subjects [21] and in the
present study, DLNO was significantly higher than predicted
whether using norms from Zavorsky and colleagues (113%
predicted, p,0.01) [34] or Aguilaniu and colleagues (107%
predicted, p = 0.011) [39]. Several subjects in both BQ and non-
BQ groups had values above the upper limit of normative data for
a variety of pulmonary function parameters. As such, we can
conclude that BQ and non-BQ were of comparable respiratory
fitness. These findings suggest that endurance training itself may
Table 2. Pulmonary function measurements for Boston Qualifiers and non-Qualifiers.
BQ (n = 10)
Non-BQ (n = 18)
Total (n = 28)
Mean
Percent Predicted
Mean
Percent Predicted
Mean
Percent Predicted
FVC (L)
5.1 (0.9)
110 (8)*
5.0 (1.0)
105 (14)
5.0 (0.9)
106 (13)*
3.8–6.4
96–124
3.4–7.2
79–134
3.4–7.2
79–134
FEV1 (L)
4.0 (0.7)
108 (11)*
3.8 (0.7)
100 (11)
3.9 (0.7)
103 (11)
2.9–5.4
96–128
2.5–5.1
86–129
2.5–5.4
86–129
FEV1/FVC
81.2 (10.6)
99 (8)
77.2 (6.3)
96 (9)
78.6 (6.2)
97 (8)
73.4–90.2
89–113
64.9–87.2
77–110
64.9–90.2
77–113
PEF (L)
9.0 (2.2)
102 (11)
10.1 (2.0)
111 (10)*
9.7 (2.1)
108 (11)*
6.0–12.9
81–118
7.0–13.1
97–137
6.0–13.1
81–137
FEF25–75 (L/s)
5.2(1.5)
133 (32)*
4.8 (1.3)
129 (29)*
5.0 (1.3)
131 (29)*
3.2–8.3
91–192
2.7–6.8
84–176
2.7–8.3
84–192
DLCO
34.7 (5.9)
113 (15)*
34.3 (6.6)
114 (14)*
34.3 (6.73)
113 (14)*
25.9–43.4
91–135
22.6–48.6
93–146
22.6–48.6
91–146
DLCO/BSA
20.0 (3.1)
–
18.3 (2.6)
–
18.9 (2.8)
–
15.5–23.9
–
13.6–23.6
–
13.6–23.9
–
DLNO
179 (27)
113 (12)*
176 (34)
113 (13)*
175 (35)
113 (13)*
140–212
97–130
124–256
94–149
120–256
94–149
DLNO/BSA
103 (14)
–
93 (13)
–
97 (14)
–
85–123
–
72–124
–
72–124
–
VC (mL)
90 (15)
116 (19)*
89 (13)
117 (15)*
90 (14)
117 (16)*
72–113
95–151
64–118
95–144
64–118
95–151
FVC: forced vital capacity; FEV1: forced expiratory volume within 1 sec; FEV1/FVC: fraction of inspired air expired within 1 sec; PEF: peak expiratory flow; FEF25–75: forced
expiratory flow during 25–75% of 6-second exhale; DLCO: pulmonary diffusing capacity for carbon monoxide, in mL/min/mmHg; DLCO/BSA: DLCO relative to body
surface area, in mL/min/mmHg/m2; DLNO: pulmonary diffusing capacity for nitric oxide, in mL/min/mmHg; DLNO/BSA: DLNO relative to body surface area, in mL/min/
mmHg/m2; VC: pulmonary capillary blood volume.
Data are reported as mean (SD) values and range.
*Denotes a significant difference in observed parameter relative to predicted (p,0.05).
doi:10.1371/journal.pone.0044513.t002
DLNO Predicts Marathon Finishing Time
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September 2012 | Volume 7 | Issue 9 | e44513
improve alveolar-capillary membrane conductance above that of
untrained individuals, but improvements in DLNO likely plateau
well before that of the heart or skeletal muscle.
Generally speaking, the lungs become limiting at a running pace
of 6:47 minutes per mile or 236 m.min21 (a 3 hour marathon).
Therefore, athletes performing at or around this pace should be
aware of the potential significance of this limitation and its
ramifications for performance. It is unknown whether any specific
training practices can be implemented to improve pulmonary
diffusion and therefore improve marathon performance.
This study is limited by its small sample size; a higher power to
detect differences in group means would likely be achieved by
recruiting more participants. Nevertheless, it is frowned upon to
conduct a post-hoc power analysis after data collection has occurred
[40,41], thus we did not perform one. Instead, confidence intervals
replace power calculations after a study is completed [40,41]. We
have provided confidence intervals in Figures 1 and 2. Addition-
ally, small group sizes result in large variances; as such, the
standard errors of the estimate for both regressions are large and
overlapping, obscuring estimation of a clear range of intersection
at which DLNO indexed to BSA begins to predict finishing time.
Larger sample sizes would also allow us to divide runners into
more specific categories by time, possibly delineating a clearer
relation between DLNO indexed to BSA and finishing time with
increasing running speed. Additionally, normalization to BSA
transforms DLNO into a variable with multiple units, possibly
complicating analysis. Mean height and body mass themselves
were not significantly different between groups; however, the
combination of these variables appears to be important when
related to pulmonary variables. It remains possible that BSA
introduces variation in the data set due to its relationship with heat
dissipation, largely dependent on stature [42]. This might have
impacted finishing time, especially in slower runners finishing as
the ambient temperature increased on race day, from about 8uC
(96% humidity) at the 8:00 AM start to 21uC (51% humidity) at
the finish line by 1:00 PM.
As pulmonary diffusion has been shown to decrease during long-
duration submaximal exercise [29,37], the efficacy of interventions
which may counter these negative effects should be explored (e.g.,
anti-inflammatory drugs or antioxidants). Our results could be
strengthened by measuring DLNO immediately after completion of
the marathon, with a greater change in DLNO representative of
presence of a limitation. Nevertheless, measurement of DLNO at
rest may still underestimate severity of diffusion limitation. As such,
future studies could also measure DLNO at submaximal speeds
during running economy testing and extrapolate these data to
marathon race pace, allowing a more accurate estimation of the
impact of diffusing capacity on running performance.
The genetic basis of DLNO could be further studied to
determine how this parameter might change as one adapts to
training. Furthermore, longitudinal and interventional studies are
recommended to determine if any specific type of training can
optimize pulmonary diffusion capacity and therefore improve
endurance running performance. More extensive understanding of
the relationship outlined in this study will allow us to confirm the
validity of diffusing capacity for nitric oxide as a fitness predictor.
In conclusion, this study found that DLNO indexed to BSA is a
better predictor of marathon finishing time in runners qualifying for
the Boston Marathon than are more commonly used variables, such
as _VO2max or running economy, but this relation was not observed
for non-BQ’s. This suggests that alveolar-capillary membrane
conductance can be pulmonary limitation in well-trained runners.
Acknowledgments
The authors would like to thank the Steamtown Marathon Race
Committee, including Assistant Race Director Jim Cummings, for help
in recruiting participants for this study. Additionally, we acknowledge the
Steamtown Marathon Medical Director, Tim Rowland, MD, for providing
available space at the medical triage area at the finish line.
Figure 1. Regression showing relation between DLNO/BSA and
marathon finishing time. For Boston Qualifiers (solid line), r2 = 0.74,
SEE = 11.8, p,0.01, showing a significant correlation. Y-intercept is
198.8+18.7 (95% confidence interval ranges from 155.7 to 242.0); slope
of the line is 20.532+0.103, with a 95% confidence interval range of
20.8 to 20.3. For non-qualifiers (dashed line), p = 0.14. Y-intercept is
135.7+26.5 (95% confidence interval ranges from 79.5 to 191.8); the
slope of the line is 20.175+0.109, with a confidence interval range of
20.4 to 0.05. The point of intersection for these lines is 178.07 minutes
(2:58:11). There is a significant difference between the correlation
coefficients of the two regressions (2-tailed z = 22.15, p = 0.03).
doi:10.1371/journal.pone.0044513.g001
Figure 2. Regression showing relation between DLCO/BSA and
marathon finishing time. For Boston Qualifiers (solid line), r2 = 0.69,
SEE = 12.8, p,0.01, showing a significant correlation. Y-intercept of the
line is 40.6+4.5, with a 95% confidence interval range of 30.2 to 51.0.
The slope of the line is 20.11+0.03, with a confidence interval of 20.18
to 20.06. For non-qualifiers (dashed line), p = 0.172. Y-intercept is
25.7+5.2, confidence interval ranges from 14.6 to 36.8. The slope of the
line is 20.03+0.02, with a 95% confidence interval ranging from 20.08
to 0.02. The point of intersection for these lines is 179.22 minutes
(2:59:14). The correlation coefficients of these lines are significantly
different (2-tailed z = 21.99, p = 0.046).
doi:10.1371/journal.pone.0044513.g002
DLNO Predicts Marathon Finishing Time
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Author Contributions
Conceived and designed the experiments: GSZ JMS. Performed the
experiments: KML AMS KAU. Analyzed the data: KML GSZ.
Contributed reagents/materials/analysis tools: GSZ. Wrote the paper:
KML GSZ AMS.
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DLNO Predicts Marathon Finishing Time
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Alveolar-membrane diffusing capacity limits performance in Boston marathon qualifiers.
Lavin, Kaleen M,Straub, Allison M,Uhranowsky, Kathleen A,Smoliga, James M,Zavorsky, Gerald S