|Year : 2017 | Volume
| Issue : 2 | Page : 104-108
Diurnal variation of peak expiratory flow rate in healthy young adults: A gender-based study
Sunil Kumar Jena1, Arati Mohanty2, Rabi Narayan Mania3, Ankita Pal4
1 Department of Physiology, VIMSAR, Burla, Odisha, India
2 Department of Physiology, IMS and SUM Hospital, Bhubaneswar, Odisha, India
3 Department of Pulmonary Medicine, IMS and SUM Hospital, Bhubaneswar, Odisha, India
4 MBBS Student, VIMSAR, Burla, Odisha, India
|Date of Web Publication||20-Apr-2017|
Sunil Kumar Jena
Department of Physiology, VIMSAR, Burla, Odisha
Source of Support: None, Conflict of Interest: None
Background: Peak expiratory flow rate (PEFR) variability follows a diurnal rhythmic pattern in healthy people as well as in asthmatics. A number of studies are there on diurnal variation of PEFR in asthmatics. However, there are fewer studies on diurnal variation in PEFR in young adult male and female in Indian population. Objective: To find out diurnal PEFR variability in young male and female separately in Indian population. Materials and Methods: Sixty-three male and 40 female medical students of age 18–24 years were recruited for this study as the participants. After proper training, PEFR recording of the participants was taken at 6–7 am, 9–10 am, 1–2 pm, 5–6 pm, and 10–11 pm by Mini-Wright peak flow meter. Recording was done by students themselves in guidance of principal investigator. Data analysis was done by unpaired t-test and one-way ANOVA. Diurnal variation of each participant was calculated by two indices, i.e., amplitude percent mean (A%M) and standard deviation percent mean (SD%M). Results: There was a significant difference in PEFR at different time periods in both male and female (P = 0.000) which shows lowest at morning followed by progressive rise in day, highest at evening, and again fall at bedtime. A%M between male and female was found significant (P = 0.019), but SD%M between male and female was not significant (P = 0.105). Conclusion: Our study provides the reference data of diurnal variation of PEFR in male and female which further will be helpful in diagnosis and monitoring of bronchial asthma patients.
Keywords: Diurnal variation, female, male, peak expiratory flow rate
|How to cite this article:|
Jena SK, Mohanty A, Mania RN, Pal A. Diurnal variation of peak expiratory flow rate in healthy young adults: A gender-based study. J Med Soc 2017;31:104-8
|How to cite this URL:|
Jena SK, Mohanty A, Mania RN, Pal A. Diurnal variation of peak expiratory flow rate in healthy young adults: A gender-based study. J Med Soc [serial online] 2017 [cited 2021 Jan 17];31:104-8. Available from: https://www.jmedsoc.org/text.asp?2017/31/2/104/204823
| Introduction|| |
The peak expiratory flow rate (PEFR) is defined as the maximum or peak flow rate that is attained during a forceful expiratory effort after taking a deep inspiration. It is expressed in liters per minute (L/min). Estimation of PEFR is a valuable parameter of air flow limitation. It measures airflow through the bronchial tree and provides an idea about bronchial tone. Estimation of PEFR has been suggested as a fare indicator of bronchial hyperresponsiveness. There is clear evidence of diurnal variation PEFR in normal individuals and this variability is exaggerated in patients of bronchial hyperreactivity. It has been suggested that diurnal variation of PEFR in excess of 20% can be used for diagnosis of bronchial asthma in remission where routine spirometry may not show any significant obstructive defect., Previous studies mentioned that PEFR shows time to time variation with respect to day and night cycle with specific pattern of lowest at early morning and highest at evening in normal as well as in asthmatics.,, PEFR variation has been widely advocated and used in clinical practice and asthma research. Still comparative studies have not sustained the claim to promote PEFR variability for diagnosing asthma because of the lack of standard cutoff value of PEFR variability for diagnosing a person as asthmatic., Number of studies are done to observe PEFR variability and most of them in patient population and older age. Very few studies are done on healthy young adults and there is not clear demarcation of gender variation of PEFR variability. We therefore designed this study to evaluate the rhythmic PEFR variability in healthy young male and female with respect to 24 h day and night cycle. This study will establish the limits of diurnal variation PEFR beyond which the variation can be considered significant.
| Materials and Methods|| |
This study was carried out in Department of Physiology, in a tertiary care teaching institute in Odisha. The study was accomplished between March 2015 and February 2016. The protocol of study was approved by the Institutional Ethical Committee. Volunteers for this study were selected from MBBS students of the same institution. One hundred and three participants were selected for this study which included 63 male and forty female. All participants having almost similar daily routine and sleep habits, nonsmokers selected randomly between the age group of 18–24 years. To avoid confounding factor, participants selected were within normal body mass index (BMI) (18–24.99 kg/m 2). A data sheet was used to fill up by the students for participant selection. The data sheet consisted of age, sex, sleeping habit, smoking history, and medication history. One hundred and forty were involved to fill up the data sheet. A thorough history taking, clinical examination, along with height and weight measurement of 140 students was done by investigators. This procedure was helpful to rule out any obvious cardiopulmonary compromise. Height and weight measurements were used for estimation of BMI. Participants with history of smoking, history of severe chest trauma, with obvious chest and spinal deformity, with personal/family history of asthma, chronic obstructive pulmonary diseases, and other cardiorespiratory diseases were excluded from the study. All participants underwent baseline pulmonary function testing to rule out pulmonary dysfunctions (restrictive and obstructive). Finally, 103 participants (63 male and forty female) were selected for this study.
All participants were explained properly about the study protocol along with the purpose and output of the study. A written consent was taken from each participant before participation in this research work. The PEFR was recorded by Mini-Wright peak flow meter (Soulgenie portable peak flow meter). Before recording the PEFR, the participants were trained about the technique of PEFR recording. For accuracy of methodology, training was essential because PEFR is a subjective method, proper training and cooperation of participants were highly valuable. During training session, each participant was instructed to stand erect and hold the instrument in horizontal position. Precaution was taken to avoid the obstruction of the pointer of the instrument by fingers while moving in the slot. They were instructed to take a deep breath, put the mouthpiece of the peak flow meter inside mouth between the upper and lower jaw, and expel the air forcefully in one blow. There should be no air leak between lips and mouthpiece of peak flow meter. All participants underwent three sessions of training in different days. Then, the recording of PEFR was done by students themselves in guidance of principal investigator for five seating at 6–7 am, 9–10 am, 1–2 pm, 5–6 pm, and 10–11 pm on same date. Each participant after three sessions of training was scheduled to perform the final recording of fixed date (1 day test) and to complete all five seating of recordings. Previous study suggested that self-recording is reliable to obtain a good reference data. At each time point, they performed three readings and the highest one was considered for analysis.
Statistical analysis was done for both male and female separately to observe the gender variation of circadian rhythm of PEFR. One-way ANOVA was used for analysis of diurnal variation of PEFR along with post hoc analysis. Unpaired t-test was used to compare baseline parameters between male and female. P < 0.05 was considered to be statistically significant. Diurnal variation of PEFR for each participant was calculated by two different indices, i.e., amplitude percent mean (A%M) and standard deviation percent mean (SD%M) by following formula.
Population mean and standard deviation (SD) of each index were calculated separately for male and female. Confidence limits were calculated to define upper limit of normal variation using population mean and SD. Statistical analysis was done by statistical software SPSS (Statistical Package for the Social Sciences, IBM Corporation, Armonk, New York, USA) version 16. For generation of tables, Microsoft Excel was used.
| Results|| |
PEFR records of 103 participants (63 male and forty female) in this study were finally analyzed. [Table 1] depicts the comparison of basic parameters, i.e., age, BMI, 6–7 am PEFR, 5–6 pm PEFR, A%M and SD%M between male and female. Mean age of male and female was 19.3 ± 0.78 years and 19.0 ± 0.87 years, respectively. Mean BMI of male and female was 21.6 ± 2.1 and 21.9 ± 1.9 kg/m 2, respectively. Mean PEFR at 6–7 am of male and female was 483 ± 55.32 and 345 ± 36.58 L/min, respectively. Mean PEFR at 5–6 pm of male and female was 547 ± 51.50 and 403 ± 42.51 L/min, respectively. Mean A%M of male and female was 13.45 ± 4.26 and 15.39 ± 3.63, respectively. Mean SD%M of male and female was 5.38 ± 1.64 and 5.89 ± 1.39, respectively.
[Table 2] depicts the diurnal variation of PEFR in male and female. PEFR was measured between 6–7 am, 9–10 am, 1–2 pm, 5–6 pm, and 10–11 pm. On analyzing the individual PEFR recordings, it was observed that PEFR was lowest at 6–7 am followed by progressive increase till evening, peak at 5–6 pm, and again fall at 10–11 pm both in male and female. In male, mean PEFR at 6–7 am was 483 ± 55.32 L/min and at 5–6 pm was 547 ± 51.50 L/min. In female, mean PEFR at 6–7 am was 345 ± 36.58 L/min and at 5–6 pm was 403 ± 42.51 L/min. The mean PEFR at different time points was analyzed for variation using one-way ANOVA. The diurnal variation of PEFR was found significant for both male (P = 0.000) and female (P = 0.000). Assuming equal variance, Tukey's test was applied which revealed significant difference in mean PEFR values of male at 6–7 am and 1–2 pm, 6–7 am and 5–6 pm, 6–7 am and 10–11 pm, 9–10 am and 5–6 pm, 5–6 pm and 10–11 pm. Tukey's test also revealed significant difference in mean PEFR values of female at 6–7 am and 9–10 am, 6–7 am and 1–2 pm, 6–7 am and 5–6 pm, 6–7 am and 10–11 pm, 9–10 am and 5–6 pm, 5–6 pm and 10–11 pm.
[Table 3] depicts the mean diurnal variation of PEFR in different indices. Mean diurnal variation in male was 13.45 ± 4.26 (A%M) and 5.38 ± 1.64 (SD%M) in this population. The upper limits of normal variability of A%M at 95% and 99% confidence limits were 14.5 and 14.84, respectively. Similarly, upper limits of SD%M at 95% and 99% confidence limits were 5.78 and 5.91, respectively. Mean diurnal variation in female was 15.39 ± 3.63 (A%M) and 5.89 ± 1.36 (SD%M) in this population. The upper limits of normal variability of A%M at 95% and 99% confidence limits were 16.51 and 16.87, respectively. Similarly, upper limits of SD%M at 95% and 99% confidence limits were 6.31 and 6.44, respectively.
|Table 3: Comparison of amplitude percent mean and standard deviation percent mean|
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| Discussion|| |
This study was conducted on healthy young adults to get preliminary reference data on diurnal variation of PEFR in male and female as an independent factor. We hypothesized to proof gender variation of circadian rhythm of PEFR in male and female separately because of clear evidence that sex is a factor that affects PEFR. Smokers were deliberately excluded from this study because smoking is known to increase diurnal variation of PEFR.,, Some researchers suggested that diurnal variation of PEFR is affected by age and elderly has higher variation.,, Thus, we selected the participants in a very narrow range of age (18–24 years). The pattern of diurnal variation of PEFR observed in this study was lowest in early morning (6–7 am) followed by a progressive rise throughout the day, highest at evening (5–6 pm), and again fall in at bedtime (10–11 pm). This variation we found was significant (P = 0.000) in both male and female. Similar pattern of variation was reported in different researchers previously, but there was no clear-cut evidence of gender variation as in our study.,,,
We expressed circadian rhythmic variation using two indices, i.e., A%M and SD%M. Different indices are available to express PEFR variability. Out of them, these two indices are the best means of expression of PEFR variability. A%M is easier to calculate, for which majority of previous studies have used it to measure diurnal variation of PEFR. However, SD%M is a better index, especially when calculating variability from <5 PEFR measurements each day. However, in our study, we used both A%M and SD%M for better data analysis. From our study, we found that significant difference in A%M between male and female. Female participants revealed higher A%M than male shown in [Table 1]. Similar results were reported by different investigators in previous studies., Another study reported that the difference A%M between male and female was not significant. Our results reported that SD%M between male and female was not significant shown in [Table 1]. Similar findings were reported by another study. The study by Aggarwal et al. suggested that in clinical practice, a diurnal variation of PEFR more than 16.5 (A%M) or 6.5% SD%M would be extremely unlikely to be seen in normal individuals. Our results reported that A%M and SD%M of male and female were below the value both in male and female reported by Aggarwal et al. Our data suggested that the upper limit of A%M in male was 14.5 and 14.85 at 95% and 99% confidence interval, respectively; A%M in female was 16.51 and 16.87 at 95% and 99% confidence interval, respectively. Upper limit of SD%M in male was 5.78 and 5.91 at 95% and 99% confidence interval, respectively; SD%M in female was 6.31 and 6.33 at 95% and 99% confidence interval, respectively.
It is seen that though the circadian rhythm in asthmatics follows a similar pattern, i.e., PEFR dip in morning, and PEFR peak in late afternoon, but the swing of PEFR from the mean value is more than in normal participants., The values of PEFR may be variable and have some limitations as the parameter is entirely effort-dependent resulting in a high intra-subject variability for population screening and clinical diagnosis of asthma. Despite the shortcomings, our findings are of interest for better understanding the effect of circadian rhythm on lung physiology and pathogenesis of pulmonary diseases, especially the diagnosis of asthma in population-based studies as well as for assessing disease severity and diagnosis.
| Conclusion|| |
This study concludes that there is significant diurnal variation in PEFR both in male and female. This information provides an idea of bronchial tone and may be considered as a useful marker in diagnosis of bronchial asthma. This knowledge may be correlated with the late night and early morning attack of bronchial asthma.
This study was done with comparatively small sample size. If the sample size was larger, we could get better appreciable information. This study also lacks the seasonal variation, for which further study may be done to observe seasonal variation of PEFR.
It was our immense pleasure to express our heartiest thanks to the participants involved in this study without whom this work could not be accomplished. Thanks to Professor and HOD Department of Physiology, for his encouragement toward this work.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Aggarwal AN, Gupta D, Chaganti S, Jindal SK. Diurnal variation in peak expiratory flow in healthy young adults. Indian J Chest Dis Allied Sci 2000;42:15-9.
Hetzel MR. The pulmonary clock. Thorax 1981;36:481-6.
Hetzel MR, Clark TJ. Comparison of normal and asthmatic circadian rhythms in peak expiratory flow rate. Thorax 1980;35:732-8.
Jamison JP, McKinley RK. Validity of peak expiratory flow rate variability for the diagnosis of asthma. Clin Sci (Lond) 1993;85:367-71.
Casale R, Pasqualetti P. Cosinor analysis of circadian peak expiratory flow variability in normal subjects, passive smokers, heavy smokers, patients with chronic obstructive pulmonary disease and patients with interstitial lung disease. Respiration 1997;64:251-6.
Thiadens HA, De Bock GH, Dekker FW, Huysman JA, Van Houwelingen JC, Springer MP, et al.
Value of measuring diurnal peak flow variability in the recognition of asthma: A study in general practice. Eur Respir J 1998;12:842-7.
Aggarwal AN, Gupta D, Kumar V, Jindal SK. Assessment of diurnal variability of peak expiratory flow in stable asthmatics. J Asthma 2002;39:487-91.
Goldstein MF, Veza BA, Dunsky EH, Dvorin DJ, Belecanech GA, Haralabatos IC. Comparisons of peak diurnal expiratory flow variation, postbronchodilator FEV(1) responses, and methacholine inhalation challenges in the evaluation of suspected asthma. Chest 2001;119:1001-10.
Thaman RG, Girgla KK, Arora GP. Circadian peak expiratory flow rate variability in healthy North Indian Geriatric population. JIACM 2010;11:195-8.
Johnston I, Anderson HR, Patel S. Variability of peak flow in wheezy children. Thorax 1984;39:583-7.
Raju PS, Prasad KV, Ramana YV, Murthy KJ. Pulmonary function tests in Indian girls – Prediction equations. Indian J Pediatr 2004;71:893-7.
Higgins BG, Britton JR, Chinn S, Lai KK, Burney PG, Tattersfield AE. Factors affecting peak expiratory flow variability and bronchial reactivity in a random population sample. Thorax 1993;48:899-905.
Boezen HM, Schouten JP, Postma DS, Rijcken B. Distribution of peak expiratory flow variability by age, gender and smoking habits in a random population sample aged 20-70 yrs. Eur Respir J 1994;7:1814-20.
Higgins B. Peak expiratory flow variability in the general population. Eur Respir J Suppl 1997;24:45S-8S.
Higgins BG, Britton JR, Chinn S, Jones TD, Jenkinson D, Burney PG, et al.
The distribution of peak expiratory flow variability in a population sample. Am Rev Respir Dis 1989;140:1368-72.
Zureik M, Liard R, Sé gala C, Henry C, Korobaeff M, Neukirch F. Peak expiratory flow rate variability in population surveys. Does the number of assessments matter? Chest 1995;107:418-23.
Jindal SK, Aggarwal AN, Gupta D. Diurnal variability of peak expiratory flow. J Asthma 2002;39:363-73.
Van Keimpema AR, Ariaansz M, Tamminga JJ, Nauta JJ, Postmus PE. Nocturnal waking and morning dip of peak expiratory flow in clinically stable asthma patients during treatment. Occurrence and patient characteristics. Respiration 1997;64:29-34.
Dikshit MB, Raje S, Agrawal MJ. Lung functions with spirometry: An Indian perspective – I. Peak expiratory flow rates. Indian J Physiol Pharmacol 2005;49:8-18.
Medarov BI, Pavlov VA, Rossoff L. Diurnal variations in human pulmonary function. Int J Clin Exp Med 2008;1:267-73.
[Table 1], [Table 2], [Table 3]