Full text of DOI:10.1592/phco.20.19.1409.34857

O RIG IN A L R ES EA RC H A RTIC LES
Peak Expiratory Flow Rate and Premenstrual Symptoms in
Healthy Nonasthmatic Women
Elaine Chong, B.Sc.(Pharm.), and Mary H. H. Ensom, Pharm.D., FASHP, FCCP
Study Objectives. To characterize intrasubject, intersubject, and diurnal
variability in peak expiratory flow rates (PEFR) of healthy nonasthmatic
women over at least one complete menstrual cycle; to determine whether a
relationship exists between PEFR and premenstrual symptoms in these
women; and to provide a forum to educate women pharmacy students by
interactive study participation.
Design. Longitudinal, investigator-blinded study.
Setting. University of British Columbia and Children ’s and Women ’s Health
Centre.
Patients. Forty healthy nonasthmatic female pharmacy students were
enrolled, and 31 (aged 22.1 ± 1.5 yrs) completed the study.
Intervention. Women were followed for at least one menstrual cycle during
which they recorded premenstrual symptom questionnaire scores daily (15
mood and physical symptoms, graded 0–3 in severity). They also measured
and recorded PEFR (3 consecutive attempts) every morning and every
evening. A feedback survey was later administered by electronic mail.
Measurements and Main Results. Thirty-one women, 28 of whom were of
Asian descent, completed the study. Over half of them (58.1%) showed
classic patterns of premenstrual symptoms, whereas PEFR fluctuated
randomly over the course of the cycle. Average coefficients of variation
(
CVs) were 4.17 ± 2.09% for morning PEFR, 3.97 ± 2.25% for evening
PEFR, and 3.72 ± 2.55% for mean daily PEFR. Average absolute diurnal
variation was 17.13 ± 12.46 L/minute, and relative diurnal variation was
3
.98 ± 2.52%. Intersubject variability for morning, evening, and mean daily
PEFRs yielded low CVs of 13.7%, 14.3%, and 13.9%, respectively. Only 14
11.3%) of 124 correlations between PEFR and premenstrual symptoms
(
were significant (p<0.05). Most participants responded positively (mean
score 3.87 on a 5-point scale) to the survey on the impact of this study.
Conclusion. Intrasubject and diurnal variability in PEFR are minimal in
nonasthmatic women; similarly, intersubject variability is relatively low.
The menstrual cycle appears to have little effect on PEFR in healthy
nonasthmatic Asian women. Pharmacy students who take part in serial
PEFR monitoring gain new appreciation for asthma and asthmatic patients.
(
Pharmacotherapy 2000;20(12):1409–1416)
Asthma is one of many medical disorders in
which cyclic exacerbations can occur during the
luteal phase of the menstrual cycle or at the onset
experience premenstrual asthma (PMA) showed
the association between exogenous estradiol
administration and improvements in asthma
1
2
of menses. Our previous study of women who
symptoms and pulmonary function. Furthermore,

1
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PHARMACOTHERAPY Volume 20, Number 12, 2000
most of the subjects had significant correlations
between asthma symptoms and premenstrual
symptoms, and approximately half also had
significant relationships between peak expiratory
flow rate or rates (PEFR) and premenstrual
clinically significant cardiovascular, neurologic,
endocrine, renal, hematologic, or gastrointestinal
diseases were excluded. Pregnant and lactating
women also were excluded.
A target sample of 40 was selected for
convenience on the basis of a previous study in
which 11 asthmatics and 29 controls recorded
3
symptoms.
Little is known about the effects of the
menstrual cycle on pulmonary function in
healthy nonasthmatic women. Nor is information
available on whether PEFR in these women is
related to premenstrual symptoms. Furthermore,
education is needed to dispel a general lack of
awareness of PMA. A prime opportunity to begin
this education is at the student level, among
future health care professionals. Thus our
objectives were to characterize intrasubject,
intersubject, and diurnal variability in PEFR of
healthy nonasthmatic women over at least one
complete menstrual cycle; to determine whether
a relationship exists between PEFR and
premenstrual symptoms in these women; and to
provide a forum to educate female pharmacy
students by interactive study participation.
4
daily diaries of asthma symptoms and PEFR. As
the primary objective of this descriptive study
was to characterize variability in PEFR of healthy
nonasthmatic women, we did not seek to detect
specific differences in PEFR and premenstrual
symptoms between asthmatics and nonasthmatics.
All subjects were properly instructed on use of
the Personal Best (Healthscan Products Inc.,
Healthdyne Technologies, Cedar Grove, NJ) peak
flow meter, followed by critiques of their practice
measurements. At home, subjects kept daily
diaries of premenstrual symptoms and PEFR for
at least one complete, uninterrupted menstrual
cycle. Premenstrual symptom questionnaires5
consisted of 15 mood and physical symptoms,
6
graded in severity from 0–3 (Figure 1). They
were completed once/day. The PEFR was
measured and recorded twice/day, with three
consecutive attempts each morning and each
evening. A feedback survey was later administered
by electronic mail (Figure 2).
Methods
Study Design and Subjects
This was a longitudinal, investigator-blinded,
clinical study. Ethics approval was obtained, and
subjects signed informed consent before
enrolling. Subjects were premenopausal women
between 18 and 45 years of age. Women were
included only if they were undergraduate
pharmacy students at the University of British
Columbia, were healthy, had regular menstrual
cycles (menses 4–7 days’ duration every 28 ± 5
days), and used a reliable method of birth control
other than oral contraceptives. Smokers, women
with excessive alcohol or drug use, or with
Data and Statistical Analysis
Demographic data were age, weight, height,
length of menstrual cycle, and length of menses.
Descriptive statistics (mean ± standard deviation
[
SD]) were used for demographic data.
The total premenstrual symptoms score was
the sum of mood and physical scores; a high
score indicated greater severity. Premenstrual
symptoms, PEFR, and diurnal variation in PEFR
From the Division of Clinical Pharmacy, Faculty of
Pharmaceutical Sciences, University of British Columbia,
and the Department of Pharmacy, Children ’s and Women ’s
Health Centre of British Columbia, Vancouver, British
Columbia, Canada (both authors).
Supported by an unrestricted educational grant from
Merck Frosst Canada, Inc., Kirkland, Quebec, Canada. Peak
flow meters were provided by Rhône-Poulenc Rorer
Pharmaceuticals Inc., Collegeville, Pennsylvania.
Mood symptom
Severity scale
❑
❑
❑
❑
❑
Anxiety/tension
Depression
Fatigue
Irritability
Mood Swings
3 = Severe; inability to perform normal
activities and subject missed work, school, or
canceled appointments.
Physical symptoms
❑
❑
❑
❑
❑
❑
❑
❑
❑
❑
Abdominal cramps
Acne
Bloating
Breast tenderness
Headache
Leg pain
Nausea
Swelling
Vomiting
Weakness
2 = Moderate; normal activities interfered with
but not to the extent that the subject missed
work or school.
Presented at the annual meeting of the American College
of Clinical Pharmacy, Kansas City, Missouri, October 26,
1
999.
Manuscript received June 21, 2000. Accepted pending
1 = Mild; interfered only slightly with normal
activities.
revisions July 26, 2000. Accepted for publication in final
form September 15, 2000.
Address reprint requests to Mary H. H. Ensom, Pharm.D.,
Department of Pharmacy (0B7), Children ’s and Women ’s
Health Centre of British Columbia, 4480 Oak Street,
Vancouver, BC, Canada V6H 3V4.
0 = None; no symptoms.
Figure 1. Premenstrual symptom questionnaire.

PEFR AND THE MENSTRUAL CYCLE Chong and Ensom
1411
were characterized over one complete cycle by
plotting them against cycle day.
(28/31, 90%) were of Asian descent; of interest,
over half (16, 52%) were Chinese. Data from one
subject were excluded due to incompleteness;
she collected data sporadically for 30 days over a
duration of 100 days, never for one consecutive
menstrual cycle. The other eight women who
did not complete the study failed to return their
data to the investigators.
Variability was assessed by coefficient of
variation (CV), which was calculated by dividing
SD by mean, multiplied by 100%. Absolute
diurnal variation was the difference between
morning and evening PEFRs in L/minute; relative
diurnal variation was absolute variation
expressed as a percentage of the highest daily
reading.
Individual data for each subject were plotted,
and linear regression analysis was used to
quantitatively evaluate the relationships between
PEFR (morning, evening, mean daily, diurnal
variation) and composite premenstrual symptoms.
Correlation coefficients were determined for each
relationship, and the test for zero correlation was
applied to indicate whether statistical significance
None of the 31 subjects reported taking any
drugs more than 3 times/month while enrolled in
the study.
Plots of composite premenstrual symptom
severity, PEFR, and diurnal variation characterized
over one complete and uninterrupted menstrual
cycle for one representative subject are presented
in Figure 3. Over half of the subjects (58.1%)
had classic patterns of premenstrual symptoms,
whereas PEFR fluctuated randomly over the
course of the cycle.
Table 2 shows a quantitative representation of
intrasubject and diurnal variability, as indicated
by CV. In general, intrasubject and diurnal
variability appear low (CV < 5%). As expected,
intersubject variability for morning, evening, and
(
defined a priori as p<0.05) had been reached.
Results
Of 40 subjects enrolled, 31 successfully
completed the study (Table 1). Most subjects
PEFR and Menstrual Cycle Study
FEEDBACK SURVEY
Participating in this
study increased my
knowledge of asthma
and my understanding
of asthmatic patients.
Participating in this
Participating in this
study increased my
awareness of gender-
based differences in
asthma that may have
important implications
for drug treatment and
patient education.
This clinical study
study increased my
appreciation for daily
monitoring (using a
peak flow meter) and
compliance issues in
asthma.
provided me a unique
learning opportunity
that will ultimately
lead to more effective
asthma management
for my future patients.
For each of the above statements, please indicate one of the following:
1
2
3
4
5
= Strongly disagree
= Disagree
= Neutral
= Agree
= Strongly agree
Figure 2. Feedback survey.

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412
PHARMACOTHERAPY Volume 20, Number 12, 2000
Table 1. Demographic Data for 31 Subjects
which is taken as the mean PEFR attainable by
healthy people of the same ethnic origin, gender,
age, and body build.
Variable
Age (yrs)
Height (cm)
Weight (kg)
Length of menstrual cycle (days)
Length of menses (days)
Ethnicity
Chinese
Other Asian
Value
1
0
22.1 ± 1.5
161.7 ± 6.4
52.2 ± 4.8
29.0 ± 2.3
5.4 ± 1.0
According to the American Thoracic Society,
many biologic sources of variation in pulmonary
1
1
function exist. Intraindividual variations may
be attributed to body position, head position,
16
13
2
Caucasian
Concurrent drugs
Acetaminophen 500 mg prn
Acetaminophen 250 mg, ASA 250 mg,
caffeine 65 mg prn
4
1
7
A
Mood symptoms
Physical symptoms
Total symptoms
6
Brompheniramine 12 mg, phenyl-
propanolamine 75 mg prn
Echinacea tincture 1 ml prn
Echinacea 350 mg capsules prn
Ibuprofen 200 mg prn
Ibuprofen 400 mg prn
Loratadine 10 mg prn
Minocycline 100 mg q.d.
Naproxen 275 mg prn
Naproxen 500 mg prn
Salbutamol 200-µg puffs prn after exercise
Triamcinolone acetonide topical prn
Unspecified topical product for leg pain
1
5
2
1
3
1
1
1
1
1
1
1
1
4
3
2
1
0
1
3
5
7
9
11 13 15 17 19 21 23 25 27 29
Cycle Day
effort dependency of maximum flow, and
Morning PEFR
Evening PEFR
Mean daily PEFR
B
440
430
420
410
400
mean daily PEFR was higher and yielded CVs of
1
3.7%, 14.3%, and 13.9%, respectively.
Table 3 shows correlation coefficients (r) that
resulted from the linear regression analysis. Four
correlations were performed for each subject, for
a total of 124. Only 14 (11.3%) of 108 correlations
showed statistically significant relationships
between PEFR and premenstrual symptoms.
Twenty-seven subjects (87%) responded to the
feedback survey. Most responded positively, with
an overall mean score of 3.87 on a 5-point scale.
They thought that the study increased their
knowledge and understanding of asthma (mean ±
SD score 3.52 ± 0.80), their appreciation for daily
monitoring and compliance (4.48 ± 0.58), and
their awareness of gender-based differences (3.41
390
380
3
70
60
3
1
3
5
7
9
11 13 15 17 19 21 23 25 27 29
Cycle Day
40
C
35
30
25
20
±
0.84), and would lead to more effective asthma
management for future patients (4.07 ± 0.68).
Discussion
15
10
5
The PEFR is an accepted marker of pulmonary
function and is widely used in respiratory
medicine.
convenient tool in the investigation and
diagnosis of occupational asthma and often is
7
Serial PEFR monitoring is a
0
1
3
5
7
9
11 13 15 17 19 21 23 25 27 29
Cycle Day
8
used alone in the assessment of asthmatic
patients. An observed PEFR is determined by
comparing it with the patient ’s predicted value,
Figure 3. Premenstrual symptoms, PEFR, and diurnal
variation in PEFR versus time profiles for a representative
subject.
9

PEFR AND THE MENSTRUAL CYCLE Chong and Ensom
1413
Table 2. Summary of Intrasubject CV and Diurnal Variations
Absolute
Diurnal
Relative
Diurnal
Morning
PEFR CV
Evening
PEFR CV
(%)
Mean Daily
PEFR CV
(%)
Variation
in PEFR
(L/min)
Variation
in PEFR
(% of maximum)
(
%)
Average
SD
4.17
2.09
3.97
2.25
3.72
2.55
17.13
12.46
3.98
2.52
Range
1.14–8.49
1.41–10.4
1.05–13.0
3.98–49.1
1.12–10.8
Table 3. Summary of Correlation Coefficients (r) for 31 Subjects
Total Symptoms
vs Absolute
Diurnal PEFR
Variation
Total Symptoms
vs Morning
PEFR
Total Symptoms
vs Evening
PEFR
Total Symptoms
vs Mean Daily
PEFR
Average
SD
0.025
0.250
-0.007
0.238
0.012
0.230
-0.029
0.213
r values for the
0.536
0.368
0.393
-0.444
0.476
0.374
0.382
-0.665
-0.465
0.349
0.397
-0.549
0.429
-0.394
1
4 subjects with
statistically
significant
relationships
circadian rhythms. In other words, PEFR may be
falsely low when the subject is supine, when the
neck is hyperextended or flexed, when
submaximum effort is given, and during the early
morning. Interindividual variability may be due
to a variety of host factors, including size (height,
weight), age, race, and past and present health.
Geographic factors, exposure to environmental
and occupational pollution (including tobacco
smoke), and socioeconomic status also may
correlated with an increased risk of ventilatory
1
5
arrest and sudden death. Two case reports, in
22- and 25-year-old students, comparable with
our subjects, noted the association between wide
diurnal variation and nocturnal wheezing in
1
6
asthmatic women.
Such variation is often
measured as the difference between highest and
lowest PEFR expressed as a percentage of the
1
2, 15, 17
highest reading each day.
In asthmatic
patients, it is classified as insignificant (< 25%),
moderate (> 25%), or large (> 50%) from the
largest variation seen for at least 2 consecutive
1
1
influence interindividual variation.
Our results showed minimal intrasubject
variability (CV < 5%). Estimates of PEFR in a
reference (nonasthmatic) population revealed
1
5
days. Another study defined abnormal diurnal
1
8
variation as more than 10%.
By these
7
, 12–14
mean CVs between 3.9% and 8.2%.
The
definitions, the value in our subjects was
insignificant (average 3.98 ± 2.25%). Even the
largest relative variation (10.8%) fell within the
limits for insignificance; however, it is debatable
whether the above asthmatic classification can be
extrapolated to the nonasthmatic population.
Furthermore, the formula for calculating diurnal
variation was used in studies where PEFR was
ninety-fifth percentile of CV, which could be used
to determine the upper limits of normal
7
, 12
variability, was 11.3–19.0%.
These
observations concur with our results; average
intrasubject CVs for our 31 subjects were 4.17 ±
2
.09% for morning PEFR, 3.97 ± 2.25% for
evening PEFR, and 3.72 ± 2.55% for mean daily
PEFR. As expected, variability among subjects is
slightly greater than CV values within the same
subject. However, intersubject CVs of 14% are
still within the upper limits of normal.
1
7
recorded at least 4 times/day, whereas our study
stipulated measurements only twice/day.
The menstrual cycle appears to have little
effect on PEFR in healthy nonasthmatic women.
We previously observed premenstrual worsening
Diurnal variations in PEFR also were low in
our subjects. Large diurnal variations were
2
of PEFR in asthmatic women, as well as a

1
414
PHARMACOTHERAPY Volume 20, Number 12, 2000
significant relationship between PEFR and
premenstrual symptoms in almost half of these
patients. In this study, intrasubject CVs for
them of disease monitoring that is integral to the
asthmatic lifestyle. By encouraging serial PEFR
monitoring, pharmacists can help patients
identify trends and teach them how to anticipate
3
PEFR were all less than or equal to those
reported in the literature for nonasthmatics. This
suggests that premenstrual PEFR worsening does
not occur in nonasthmatic women. In other
words, our determinations of menstrual cycle-
related intrasubject variability in PEFR are
similar to those reported in the literature, which
did not consider the influence of the menstrual
1
worsening of asthma.
To our knowledge, this study was one of the
first to educate pharmacy students by encouraging
their participation as subjects. An earlier
investigation showed that traditional, didactic,
drug-related education increased factual
knowledge but had few effects on attitudes
1
3, 14
20
cycle.
One group found significantly lower
among pharmacy students.
Since today’s
PEFR during the premenstrual phase in 14
pharmacy students are tomorrow ’s pharmacists,
attitudes and complete understanding of the
patient are vital for better pharmacy practice.
Over 88% of our subjects agreed or strongly
agreed that this learning opportunity ultimately
would lead to more effective asthma management
for future patients. This implies that other
disease states may be effectively and successfully
appreciated through innovative and interactive
teaching methods.
1
9
healthy medical students. Unfortunately, that
research had unclear inclusion and exclusion
criteria, small sample, pulmonary function
testing only twice/week, and inadequate length of
follow-up. With prospective daily documentation,
PEFR did not appear to vary during the course of
the menstrual cycle in our subjects. This concurs
with an earlier study in which no significant
menstrual cycle-related changes in symptoms,
peak flow rates, spirometric parameters, or
airway reactivity were observed in healthy
Our study had several limitations, including a
specific subject population and compliance
issues. Subjects were all healthy university
students in their early to middle twenties. Thus,
our results should not be extrapolated far from
this limited population. Furthermore, most
subjects were Asian, and ethnicity is consistently
an important determinant of pulmonary
4
controls (nonasthmatics). With only 11.3% of
correlations between PEFR and premenstrual
symptoms being significant, there appears to be
little association between the variables.
Current research validates the findings of our
2
, 3
previous studies.
Since PEFR in healthy
1
1
nonasthmatic women does not seem to be
affected by the menstrual cycle, premenstrual
worsening in asthmatic women is specific to that
population. This study in nonasthmatic women
provides important baseline knowledge of PEFR
that should be taken into account during future
investigations of asthmatic women.
function.
Compared with Caucasians of
European descent, PEFR for most other races are
1
1
usually smaller. Normal values for PEFR in
adult Chinese women aged 20–24 years were
2
1, 22
reported as 404 ± 43 to 417 ± 36 L/minute,
compared with 444–497 L/minute reported in the
Personal Best peak flow meter insert. These
lower values were observed among our
predominantly Asian subjects.
Pharmacy students who took part in serial
PEFR monitoring gained new appreciation for
asthma. With the current shift from disease
treatment to disease prevention, monitoring has
become an integral concern of health care
professionals. Students are in a prime position to
learn more about patient education, and our
study provided a forum for this purpose. Many
participants mentioned how difficult it was to
comply with taking PEFR measurements
twice/day. Of interest, over 96% of subjects
agreed or strongly agreed that participation in
this study increased their appreciation for daily
monitoring and compliance issues in asthma.
The positive response to the feedback survey
indicates that students benefited from this
learning opportunity. The experience appears to
have cultivated better understanding among
The two non-Asian subjects had intrasubject
variabilities in mean daily PEFR of 3.04 ± 0.52%,
and diurnal variabilities of 18.70 ± 0.85 L/minute
(absolute variation) and 4.81 ± 0.42% (relative
variation). These values were not considered
outliers compared with those of Asian subjects.
Omitting their measurements from the overall
analysis did not alter intersubject variability
(14.0%) from the value calculated from all 31
subjects (13.9%). Nevertheless, many studies of
PEFR do not stratify subjects according to
ethnicity, and caution should be exercised in
interpreting such results.
Notably, a few subjects had larger changes
between morning and evening PEFR and for each
of three consecutive attempts compared with

PEFR AND THE MENSTRUAL CYCLE Chong and Ensom
1415
pulmonary function, and ␤ -receptors. Pharmacotherapy
other subjects. This inconsistency may indicate
lack of expertise using the peak flow meter
accurately, although all subjects demonstrated
proper use of the instrument at the time of
enrollment. The literature suggests reproducibility
criteria (two highest readings within 10% of each
other) to be acceptable when performing
2
1
997;17:224–34.
3
4
5
. Ensom MHH, Chong E, Carter D. Premenstrual symptoms in
women with premenstrual asthma. Pharmacotherapy
1
999;19:374–82.
. Pauli BD, Reid RL, Munt PW, Wigle RD, Forkert L. Influence
of the menstrual cycle on airway function in asthmatic and
normal subjects. Am Rev Respir Dis 1989;140:358–62.
. Mortola JF, Girton L, Beck L, Yen SS. Diagnosis of
premenstrual syndrome by a simple, prospective, and reliable
instrument: the calendar of premenstrual experiences. Obstet
Gynecol 1990;76:302–7.
1
3, 23
successive measurements.
Moreover,
formulas for calculating diurnal variation often
1
7
6
. Eliasson O, Scherzer HH, DeGraff AC Jr. Morbidity in asthma
in relation to the menstrual cycle. J Allergy Clin Immunol
employ at least four measurements of PEFR/day,
whereas our study stipulated only two.
1
986;77:87–94.
Subject compliance was an important part of
this clinical study. Daily data collection of PEFR
and premenstrual symptoms depended on
accurate documentation in diaries. Most subjects
were surprised at the dedication required for
compliance. Self-reporting through diary docu-
7
8
. Higgins B. Peak expiratory flow variability in the general
population. Eur Respir J 1997;10(suppl 24):45s–8.
. Lee HS. Serial peak expiratory flow rate monitoring—a useful
tool in epidemiological studies on occupation asthma. Ann
Acad Med Singapore 1994;23:725–30.
9. Gautrin D, D’Aquino LC, Gagnon G, Malo J-L, Cartier A.
Comparison between peak expiratory flow rates (PEFR) and
FEV1 in the monitoring of asthmatic subjects at an outpatient
clinic. Chest 1994;106:1419–26.
10. Nunn AJ, Gregg I. New regression equations for predicting
peak expiratory flow in adults. Br Med J 1989;298:1068–70.
2
4–26
mentation is reported both to overestimate
2
7
and correlate highly with actual compliance as
determined by electronic monitoring. Moreover,
compliance can be improved through a
structured program of supervision and periodic
1
1. American Thoracic Society. Lung function testing: selection of
reference values and interpretative strategies. Am Rev Respir
Dis 1991;144:1202–18.
2
6
12. Quackenboss JJ, Lebowitz MD, Krzyzanowski M. The normal
range of diurnal changes in peak expiratory flow rates. Am Rev
Respir Dis 1991;143:323–30.
13. Hegewald MJ, Crapo RO, Jenson RL. Intraindividual peak flow
variability. Chest 1995;107:156–61.
retraining. Methods that require more than two
measurements each day for long periods of data
2
8, 29
collection will suffer from low compliance.
However, all subjects in this study were
pharmacy students and were aware of compliance
issues. Women who completed the study
expressed a strong interest in the research and in
their own education; less-compliant women were
excluded from the data analysis either because
their data were incomplete or because they failed
to return their study diaries.
1
4. Lebowitz MD, Knudson RJ, Robertson G, Burrows B.
Significance of intraindividual changes in maximum expiratory
flow volume and peak expiratory flow measurements. Chest
1
982;81:566–70.
1
5. Hetzel MR, Clark TJH, Branthwaite MA. Asthma: analysis of
sudden deaths and ventilatory arrests in hospital. Br Med J
1977;1:808–11.
1
1
6. Bateman JRM, Clarke SW. Sudden death in asthma. Thorax
1
979;34:40–4.
7. European Academy of Allergology and Clinical Immunology.
Guidelines for the diagnosis of occupational asthma. Clin Exp
Allergy 1992;22:103–8.
Summary
1
1
2
8. Boezen HM, Schouten JP, Postma DS, Rijcken B. Relation
between respiratory symptoms, pulmonary function and peak
flow variability in adults. Thorax 1995;50:121–6.
9. Rao GS, Rajan P, Walter S. Expiratory flow rate changes during
the menstrual cycle [letter]. Indian J Physiol Pharmacol
Intrasubject and diurnal variability in PEFR is
minimal in nonasthmatic women; similarly,
intersubject variability is relatively low. The
menstrual cycle appears to have little effect on
PEFR in healthy, nonasthmatic, Asian women.
Pharmacy students who take part in serial PEFR
monitoring gain a new appreciation for asthma.
1
991;35:74–6.
0. Stenmark DE, Kinder BN, Milne LD. Drug-related attitudes
and knowledge of pharmacy students and college
undergraduates. Int J Addict 1977;12:153–60.
2
2
1. Da Costa JL, Goh BK. Peak expiratory flow rate in normal
adult Chinese in Singapore. Singapore Med J 1973;14:511–14.
2. Lam KK, Pang S-C, Allan WGL, et al. A survey of ventilatory
capacity in Chinese subjects in Hong Kong. Ann Hum Biol
Acknowledgments
1
982;9:459–72.
This study was made possible by volunteer
participation of 40 undergraduate pharmacy students
at the University of British Columbia who served as
subjects.
23. Dahlquist M, Eaisen EA, Wegman DH, Kriebal D.
Reproducibility of peak expiratory flow measurements. Occup
Med 1993;8:295–302.
2
4. Straka RJ, Fish JT, Benson SR, Suh JT. Patient self-reporting of
compliance does not correspond with electronic monitoring: an
evaluation using isosorbide dinitrate as a model drug.
Pharmacotherapy 1997;17:126–32.
References
2
5. Berg J, Dunbar-Jacob J, Rohay JM. Compliance with inhaled
medications: the relationship between diary and electronic
monitor. Ann Behav Med 1998;20:36–8.
1
. Ensom MHH. Gender-based differences and menstrual cycle-
related changes in specific diseases: implications for
pharmacotherapy. Pharmacotherapy 2000;20:523–39.
26. Murata GH, Kapsner CO, Lium DJ, Busby HK. Patient
compliance with peak flow monitoring in chronic obstructive
pulmonary disease. Am J Med Sci 1998;315:296–301.
2
. Chandler MHH, Schuldheisz S, Phillips BA, Muse KN.
Premenstrual asthma: the effect of estrogen on symptoms,

1
416
PHARMACOTHERAPY Volume 20, Number 12, 2000
2
7. Gong H Jr, Simmons MS, Clark VA, Tashkin DP. Metered-dose
inhaler usage in subjects with asthma: comparison of Nebulizer
Chronolog and daily diary recordings. J Allergy Clin Immunol
populations: methodology. Eur Respir J 1997;10(suppl
24):42s–4.
29. Cote J, Cartier A, Malo J-L, Rouleau M, Boulet L-P.
Compliance with peak expiratory flow monitoring in home
management of asthma. Chest 1998;113:968–72.
1
988;82:5–10.
2
8. Britton J. Measurement of peak flow variability in community