J Appl Physiol 97: 821-826, 2004.
First published April 23, 2004; doi:10.1152/japplphysiol.01403.2003
8750-7587/04 $5.00
Effect of body size on breathing pattern and fine-particle deposition in children
William D. Bennett and
Kirby L. Zeman
Center for Environmental Medicine, Asthma and Lung Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
Submitted 30 December 2003
; accepted in final form 13 April 2004
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ABSTRACT
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Interchild variability in breathing patterns may contribute to variability in fine particle lung deposition and morbidity in children associated with those particles. Fractional deposition (DF) of fine particles (2-µm monodisperse, carnauba wax particles) was measured in healthy children, age 6–13 yr (n = 36), while they followed a resting breathing pattern previously determined by respiratory inductance plethysmography. Interchild variation in DF, measured by photometry at the mouth, was most strongly predicted by their tidal volume (VT) (r =0.79, P < 0.001). Multiple regression analysis further showed that, for any given height and age, VT increased with increasing body mass index (BMI) (P < 0.001). The overweight children (
95th percentile BMI) (n = 8) had twice the DF of those in the lowest BMI quartile (<25th percentile) (n = 9; 0.28 ± 0.13 vs. 0.15 ± 0.06, respectively; P < 0.02). In the same groups, resting minute ventilation was also significantly higher in the overweight children (8.5 ± 2.2 vs. 5.9 ± 1.1 l/min; P < 0.01). Consequently, the rate of deposition (i.e., particles depositing/time) in the overweight children was 2.8 times that of the leanest children (P < 0.02). Among all children, the rate of deposition was significantly correlated with BMI (r = 0.46, P = 0.004). These results suggest that increased weight in children may be associated with increased risk from inhalation of pollutant particles in ambient air.
aerosol deposition; inhalation toxicity; inhaled particles
EPIDEMIOLOGICAL STUDIES HAVE LINKED particulate air pollution to acute increases in morbidity among children (17, 19, 21). Although many of these studies have primarily found effects in children with indications of preexisting respiratory illness such as asthma (17, 27), some have also noted effects in children with healthy lungs (19). Chronic effects of fine particulate matter (particles of <2.5 µm) on lung growth in healthy children have also been found (9). Although most mortality studies have primarily shown such effects in elderly adults, especially those with preexisting cardiorespiratory disease, recent studies have also shown increased mortality in children in association with increased particulate matter (7). Although children may be more susceptible to the biological effects of particulate matter, these morbidity/mortality effects may be further enhanced by increased fractional deposition (DF) of inhaled particles in the lower respiratory tract of children. Little data exist for either DF of inhaled particles or breathing patterns and their relationship to DF in children.
Both lung growth with age and changes in breathing patterns may affect the DF of inhaled particles (2, 3, 12). Changes in alveolar surface area normalized to lung volume with age suggest a decreasing mean alveolar diameter with increasing age to 
30 yr (25). On the other hand, tracheobronchial airways grow in length and diameter from birth to adulthood (25). Breathing patterns also change with increasing age from child to adult, i.e., tidal volumes (VT) increase and respiratory rates decrease (14, 23, 26). Based on these data, particle deposition models predict increasing deposition in the pulmonary region of the lung but decreasing tracheobronchial deposition as children age to adulthood (13). As a result, the model predicts little difference in total DF between children and adults for nearly all inhalable particles.
In previous studies (10, 14), to assess breathing pattern variables among children, the children breathed on a mouthpiece with a noseclip. Yet it is known that breathing patterns in both adults and children (11, 23) are affected by the use of a mouthpiece. More realistic breathing patterns can be obtained by use of respiratory inductance plethysmography (RIP) (18, 23, 26). Schiller-Scotland et al. (20) found higher deposition of inhaled particles (50%) in children (age 3–14 yr) compared with adults for spontaneous breathing on a mouthpiece. However, the reported minute ventilations (
E) in these children were much higher than might be expected (23), which suggests that these children may have been breathing more deeply than normal on the mouthpiece apparatus (23, 11). This would have contributed to an increased DF in these children (3).
We recently compared the DF of fine particles in children (age 7–13 yr), adolescents (age 14–18 yr), and adults (age 19–35 yr) for mouth-breathing conditions (4). In contrast to previous deposition studies (1, 20), we measured DF of inhaled, fine (2-µm aerodynamic diameter) particles in all subjects as they breathed the aerosol with a pattern previously determined by RIP in each individual at rest (5, 6), i.e., that subject's "real" resting breathing pattern. Breath-by-breath DF (ratio of particles not exhaled to total particles inhaled) was determined by photometry at the mouth. Unlike the Schiller-Scotland et al. study (20), we found no difference in DF for the children vs. adults for these fine particles. On the other hand, the rate of deposition (Drate) normalized to lung surface area tended to be greater (35%) in the children vs. the combined group of adolescents and adults for resting breathing of these particles. The variable Drate normalized to lung surface area is a function of the DF, the subject's E, and his/her lung size. The increased Drate normalized to lung surface area in the children was due to their higher E in relation to their lung volume. Among the children, DF was shown to be dependent on interchild variation in VT. Unfortunately, in our previous study, an insufficient number of children was studied (n = 16) to assess the dependence of spontaneous breathing patterns and associated fine-particle deposition on age, gender, or anthropometric factors among these preadolescent children.
The purpose of the present study was to extend our previous study to a larger group of healthy children (age 6–13 yr) to assess age, gender, and anthropometric factors that might affect both spontaneous breathing pattern and fine-particle deposition in healthy children. We hypothesize that these factors influence breathing pattern and particle deposition in preadolescent children. As with our previous studies, we measured DF of inhaled, fine (2-µm aerodynamic diameter) particles in all children as they breathed the aerosol with a pattern determined by RIP in each individual at rest (4–6). In addition to breathing pattern variables, i.e., VT, flows, and breathing frequency associated with their spontaneous resting breathing, we also measured pulmonary function and morphometric parameters in each child.
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METHODS
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Subjects.
Thirty-six (20 boys, 16 girls) children (age 6–13 yr; mean ± SD, 10.3 ± 2 yr) were studied. They had no history of lung disease and no recent history of acute respiratory infection or viral illness within the previous 4 wk. Informed assent and consent was obtained from each child and his/her parent; the study had the approval of the University of North Carolina Committee on the Protection of the Rights of Human Subjects. Individual raw data (anthropometric, lung volumes, pulmonary function, and deposition data) may be obtained through the principal author for use in dose-risk modeling.
Lung function measurements.
We initially measured routine pulmonary function parameters for each child. Forced expiratory volume in 1 s, forced vital capacity, inspiratory capacity, and expiratory reserve volume were determined for each subject by spirometry. Functional residual capacity (FRC), airway resistance (Raw), and specific Raw were measured by body plethysmography. Total lung capacity was determined from the sum of FRC and inspiratory capacity, and residual volume as the difference between FRC and expiratory reserve volume measurements.
Effective airspace diameter measurements.
In each subject, we used the single breath aerosol recovery technique to estimate an effective airspace diameter associated with airways in the region of transition from bronchioles to alveolated airspaces in the lung (EADtrans) (29). The technique used in these experiments is described in detail elsewhere (3, 28, 29). In brief, the EADtrans was determined by analysis of exhaled aerosol concentrations as a function of exhaled volume after inspiratory capacity breaths of an aerosol with breath holds at total lung capacity for 0–10 s. A 1-µm [mass median aerodynamic diameter (MMAD)] monodisperse aerosol [geometric standard deviation (
g) = 1.1] composed of Carnauba wax and salt nuclei was generated by a condensation aerosol generator (MAGE) for use in these measurements. The technique for measuring particle concentration and inhaled/exhaled volume is described in DF measurements. Assuming the lung is composed of a system of randomly oriented tubes, the rate of decline (slope) of the recovery vs. breath-hold time relationship is inversely proportional to the mean effective diameter of those tubes (3, 28, 29).
Breathing pattern measurements.
Each subject's spontaneous resting breathing pattern was measured by RIP (Respitrace, Ambulatory Monitoring). This technique avoids changes in breathing pattern induced by breathing on a mouthpiece and thus more accurately measures normal, spontaneous breathing patterns (11, 23). The child was fitted with elastic inductance bands around the chest and abdomen. The changes in inductance of these bands with expansion and contraction were calibrated to spirometry according to the procedure of Tobin et al. (26). All signals, from the two bands and the spirometer, were collected at 20 Hz and analyzed on a Macintosh computer using Superscope (GW Instruments) data acquisition/analysis software. After calibration procedures, the RIP signals of a 4-min period of resting spontaneous breathing were recorded for each child while he/she sat upright. Fourier analysis of the RIP waveform provided the dominant frequency of breathing. A minimum of seven consecutive breaths were analyzed in a region of the breathing waveforms that corresponded closest to this dominant frequency to determine the mean VT and breathing period (T) for that individual.
DF measurements.
Measurements of DF for a 2-µm (MMAD) monodisperse (g = 1.15) aerosol (carnauba wax) were made in each child using light-scattering photometry at the mouth (3, 4–6, 12, 20). The mouthpiece was attached to a light-scattering photometer positioned perpendicular to the airstream for measuring particle concentration during inhalation and exhalation. Tidal flow was measured with a Fleisch no. 1 pneumotachograph, and the flow signal was integrated to provide a continuous measure of volume. Number of particles inhaled and exhaled was determined by
 | (1) |
where is tidal flow, C is concentration, Nin is the number of particles inhaled, Nex is the number of particles exhaled, and TI and TE are inspiratory and expiratory times, respectively.
DF, then, was calculated as
 | (2) |
In each child, DF was measured for his/her "real" resting breathing pattern, previously measured by RIP (4–6). Subjects were trained to control their inhaled/exhaled volume (integrated from the pneumotach signal and displayed on an oscilloscope) and breathing rate to match a sinusoidal pattern created by a signal generator (also displayed on the oscilloscope). The oscilloscope patterns were set via the signal generator to mimic the individual child's breathing pattern in terms of VT and T, as previously measured by RIP. Once the children were trained to follow their specific pattern, the aerosol was introduced to them via a three-way valve. DF was measured for each breath during a 30-s period. Mean DF was determined from two 30-s periods of measurements (i.e., a total of 10–15 breaths depending on the child's breathing frequency). For each period of measurement, the first breath was excluded from the calculated mean DF to remove the effects of filling dead-space volume in the sampling chamber. Within each 30-s sample period, at least three breaths with targeted VT and breathing rate were selected for DF analysis. Breaths that did not closely match the targeted VT and breathing rate were discarded. Associated measurements of mean VT and T were also determined for each average DF.
Previous studies show that DFs calculated from the first few breaths of an inhaled fine aerosol (0.5-µm MMAD) are slightly greater than later breaths due to an initial "wash-in" effect (24). Theoretical analyses (24) suggest that as many as 10 breaths might be required to reach a steady-state DF. The decision to restrict measures to a 30-s period in the present study was based on 1) the inability of children to maintain controlled breathing for longer periods and 2) the desire to minimize carnauba wax aerosol exposure to the children. Although we could not always select breaths for DF analysis at the end of the sampling period (i.e., to minimize wash-in effects), analyzed breaths were randomly distributed throughout the sampling period so that there was no bias among the children. Furthermore, in those children who had very reproducible controlled breaths, the mean DF for the 2-µm particles reached a plateau/steady state after two breaths of aerosol inhalation. Thus, as expected, the mixing contribution to DF for 2-µm particles is a lesser fraction than is observed with smaller 0.5-µm particles (24).
DFs provide an estimate of breath-by-breath dose to the lung, but the more relevant parameter for determining total lung dose for any child is given by Drate, i.e., deposited particles/time
 | (3) |
where C is the airborne concentration of particles. Drate (where C is a constant) was calculated for each child using the E associated with the DF measurements.
Statistical analysis.
A multivariate backward stepwise regression (Systat for Macintosh) for breathing-pattern variables (VT, T, and E) was performed considering their dependency on the variables of age, height, and body mass index (BMI). A similar regression was performed for DF dependency on the following variables: VT, T, FRC-to-total lung capacity ratio, Raw, EADtrans, age, height, and BMI. Due to our limited data set, we did not consider interactions between variables for these analyses. Statistical criteria for a variable to enter and stay in the stepwise model was set at P = 0.15. Group comparisons among subsets of children were made by independent samples t-test.
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RESULTS
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Tables 1–3 show the results of the regression analysis for spontaneous resting breathing patterns (VT, T, and E measured by RIP) as a function of height, BMI, and age. Although both VT (0.308 ± 0.096 liter) and T (3.06 ± 0.48 s) were a function of a child's height, they were also significantly predicted by the child's BMI. Figure 1 illustrates the relationship between BMI and VT (r = 0.72, P < 0.001) among all children. Only BMI significantly (P < 0.05) predicted E (6.1 ± 1.7 l/min) among the children. The negative coefficient with age in the regression analyses (Tables 1 and 3) suggests that once height and BMI were taken into account, VT and E were slightly reduced with age in this range of children. Age, height, and BMI were matched by gender, and there were no gender differences in RIP measurements of VT, T, and E among the children.
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Fig. 1. Tidal volume (VT) as a function of body mass index in the children. Solid line shows line of best fit.
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Table 4 provides a summary of how well the children were able to accomplish the task of breathing the particles for the DF measurements in the same manner as they breathed normally at rest as measured by RIP. It shows the mean breathing patterns for the children 1) as measured by RIP vs. 2) the pattern associated with the DF measures when children were attempting to reproduce their RIP pattern and 3) correlation coefficients between the RIP- and DF-associated breathing parameters. The children matched their T very well. There was also a very good correlation for VT between the two measures, although the children did tend to overshoot their target VT from the RIP measures when inhaling the particles for DF measures. The difference was 15% on average, but it was relatively constant across the entire intersubject range in VT (i.e., intercept of regression was 0.053 liter, consistent with the average difference of 0.047 liter).
The mean DF for all children was 0.22 ± 0.10. There was no difference in DF between boys and girls (0.22 ± 0.10 vs. 0.22 ± 0.11, respectively). Multiple regression analysis of DF as a function of breathing parameters associated with the DF measures, lung function/morphometry, and anthropometric factors showed both VT and EADtrans were significant predictors of DF, i.e., DF increased with increasing VT and decreasing EADtrans. Table 5 provides regression coefficients, statistical significance, and the range of values for each variable. VT was the most significant predictor of DF among the children. Figure 2 illustrates the relationship between VT (associated with the DF measures) and DF (r = 0.79, P < 0.001). In accordance with the association between spontaneous VT and BMI (Fig. 1), DF and BMI were also significantly correlated (r = 0.47, P = 0.004).
As with DF, Drate was not significantly different between boys and girls but was also significantly correlated with BMI (r = 0.46, P = 0.004). Table 6 shows a summary of the children categorized in three groups by percentile BMI for their age (16): <25, 25–94, and 95 percentile. This latter group is defined as being overweight by the National Center for Health Statistics (16). VT, DF, E, and Drate were all significantly greater in the highest vs. lowest percentile BMI group. Neither age nor height was different among the three groups.
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DISCUSSION
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In healthy children, age 6–13 yr, we found that interchild variation in VT was significantly predicted by height, BMI, and age. At any given height and age, VT increased with increasing BMI. Multivariate relationships between spontaneous breathing patterns measured by RIP and body size, age, and gender in children have not been previously investigated. In fact, the nature of children's spontaneous breathing patterns has been little studied (e.g., Refs. 10, 14, 23,). Both Jammes et al. (14) (ages 6–80 yr) and Gaultier et al. (10) (ages 4–16 yr) assessed breathing-pattern variables as a function of age, height, and body weight. However, neither performed multivariate analyses in their studies but rather assessed simple linear correlations, e.g., between VT (or frequency of breathing) vs. subject characteristics. For example, Jammes et al. (14) reported a positive relationship between VT and age (from child to young adult) that could easily be explained by similar strong relationships (also reported) with height and body weight, both of which strongly correlate with age in the child to young adult range. In fact, when Gaultier et al. (10) normalized VT to body weight, there was a slight decrease in this variable as a function of age among the children, similar to our findings. As discussed previously (11, 18, 23), a difficulty with both of these studies arises from having the subjects breathe via a mouthpiece during breathing-pattern measurements. It has been shown that breathing patterns in both adults and children are affected by the use of a mouthpiece (VT increases and breathing frequency decreases). More realistic patterns can be obtained by use of RIP (18, 23, 26), as we have done in our study. Our data would suggest that the increasing VT with age among children is most strongly related to children's height rather than age per se. The deeper breathing associated with the heavier children is reflected in their increased resting E compared with the leaner children (Tables 3 and 6) and may reflect a greater metabolic need at rest in these children. The mean resting VT and breathing rates for children reported here are similar to those found previously by Tabachnik et al. (23), who also used RIP (mean VT = 0.314 liter and T = 3.05 s). Yet Tabachnik et al. did not study a sufficient number of children to assess dependency on age, gender, and anthropometric factors. In addition, our mean breathing patterns in children compared with mean RIP-derived resting VT and breath period in young adults are 0.383 liter and 3.60 s, respectively (26).
We also found that DFs of 2-µm MMAD inhaled particles for oral breathing under spontaneous resting conditions increased with increasing VT and decreasing airspace sizes (Table 5, Fig. 2). This is consistent with our earlier finding in a smaller group of children (4). Unlike previous studies to measure DF of inhaled particles in children (1, 20), we first measured each child's resting breathing pattern by RIP to use in the measures of DF (4–6). All children were able to match their breathing rates fairly well while breathing the particles (Table 4). The slight over-inhalation during DF measures likely resulted in a modest increase in DF to what might have been expected if VT had been matched exactly between DF and RIP measures (by 0.04 based on the slope of the DF vs. VT relationship in Fig. 2 and the intercept of the difference in VT between the 2 measures). The desire to breathe deeper than usual when breathing on a mouthpiece has been observed in many studies of this kind (5, 11,18, 23). These same studies in adults also showed that respiratory rate was decreased when breathing on a mouthpiece compared with RIP measures [mean 25% (11) and 29% (18) decrease]. These studies suggest that our attempts to have the children control their VT and breathing rates to approximate spontaneous values resulted in breathing patterns that more closely approximated spontaneous resting breathing. The average DF for resting breathing of 2-µm particles associated with our larger cohort of children (0.22) is the same as that measured in our previous comparison to adults (4), who also had a mean DF of 0.22. Although the smaller airway sizes of children vs. adults may lead to increased deposition of fine particles in children, the increased respiratory rate in children tends toward a decrease in DF compared with adults (4, 13). Consequently, for 2-µm particles, the mean DF for resting breathing in children vs. adults is similar.
Because DF was most strongly predicted by VT, this finding suggested that DF also increased with increasing BMI. Table 6 shows that the children in the highest-percentile BMI (i.e., age adjusted) had almost twice the DF of the children in the lowest-percentile BMI. Moreover, because the overweight children also breathed with higher E at rest, their total Drate was nearly three times higher than the leanest children (Table 6). The results of this study suggest that overweight children may be at increased risk for respiratory morbidity associated with the inhalation of pollutant particles in ambient air. It is important to note that our data have only been determined for fine particles under resting breathing conditions. Furthermore, the children recruited for study have not included obese children (BMI > 30). Obesity has recently been shown to be associated with both the incidence of asthma symptoms and initial onset of asthma in children (8, 15). Whether asthma predisposes one to obesity or vice versa is not clear. Such children may have even greater total deposition in their lungs due to increased Raw and expiratory flow limitation (6, 22), especially in their airways where the presence of asthma pathology may further predispose to increased reactivity in these children. Further study is needed to determine whether fine-particle deposition in obese children is increased relative to leaner children. Enhanced particle deposition may further exacerbate preexisting asthma, resulting in increased frequency of symptoms.
In conclusion, we have shown that interchild variability in fine-particle deposition at rest is strongly dependent on breathing pattern, specifically inhaled VT, and to a lesser extent on peripheral airspace sizes. Spontaneous resting VT is dependent on a child's height and age, but once these factors are taken into account BMI is a strong predictor of VT, i.e., increasing VT with increasing BMI. As a result, the overweight children have significantly higher fine-particle deposition at rest, nearly three times that of the leanest children. These results suggest that overweight children may be at increased risk associated with inhaled particulate matter.
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GRANTS
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This study was supported by US EPA Cooperative Agreement CR824915
[GenBank]
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ACKNOWLEDGMENTS
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This study was performed in laboratories of the US Environmental Protection Agency (EPA). It has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
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FOOTNOTES
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Address for reprint requests and other correspondence: W. D. Bennett, Center for Environmental Medicine, CB 7310, 104 Mason Farm Rd., Univ. of North Carolina at Chapel Hill, Chapel Hill, NC 27599. (E-mail: william_bennett{at}med.unc.edu
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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REFERENCES
|
|---|
- Becquemin MH, Roy M, Bouchikhi A, and Teillac A. Deposition of inhaled particles in healthy children. In: Proceedings of the 2nd Int. Symposium on "Deposition and Clearance of Aerosols in the Human Respiratory Tract," Salzburg, Austria, edited by Hofmann W. Wien, Austria: Facultas, 1987, p. 18–20.
- Bennett WD. Human variation in spontaneous breathing deposition fraction: a review. J Aerosol Med 1: 67–80, 1988.
- Bennett WD and Smaldone GC. Human variation in the peripheral air-space deposition of inhaled particles. J Appl Physiol 62: 1603–1610, 1987.[Abstract/Free Full Text]
- Bennett WD and Zeman KL. Deposition of fine particles in children spontaneously breathing at rest. Inhal Toxicol 10: 831–842, 1998.[CrossRef]
- Bennett WD, Zeman KL, and Kim CS. Variability of fine particle deposition in healthy adults: effect of age and gender. Am J Respir Crit Care Med 153: 1641–1647, 1996.[Abstract]
- Bennett WD, Zeman KL, Kim CS, and Mascarella J. Enhanced deposition of fine particles in COPD patients spontaneously breathing at rest. Inhal Toxicol 9: 1–14, 1997.
- Conceicao GM, Miraglia SG, Kishi HS, Saldiva PH, and Singer JM. Air pollution and child mortality: a time-series study in Sao Paulo, Brazil. Environ Health Perspect 109, Suppl 3: 347–350, 2001.
- Figueroa-Munoz JI, Chinn S, and Rona RJ. Association between obesity and asthma in 4–11 year old children in the UK. Thorax 56: 133–137, 2001.[Abstract/Free Full Text]
- Gauderman WJ, Gilliland CF, Vora H, Avol E, Stram D, McConnell R, Thomas D, Lurmann F, Margolis HG, Rappaport EB, Berhane K, and Peters JM. Association between air pollution and lung function growth in Southern California children. Am J Respir Crit Care Med 162: 1383–1390, 2000.[Abstract/Free Full Text]
- Gaultier C, Perret L, Boule M, Buvry A, and Girard F. Occlusion pressure and breathing pattern in healthy children. Respir Physiol 46: 71–80, 1981.[CrossRef][ISI][Medline]
- Gilbert R, Auchincloss JH, Brodsky J, and Boden W. Changes in tidal volume, frequency, and ventilation induced by their measurement. J Appl Physiol 33: 252–254, 1972.[Free Full Text]
- Heyder J, Gebhart J, and Scheuch G. Influence of human lung morphology on particle deposition. J Aerosol Med 1: 81–88, 1988.
- Hofmann W, Martonen TB, and Graham RC. Predicted deposition of nonhygroscopic aerosols in the human lung as a function of subject age. J Aerosol Med 2: 49–68, 1989.
- Jammes Y, Auran Y, Gouvernet J, Delpierrre S, and Grimaud C. The ventilatory pattern of conscious man according to age and morphology. Bull Eur Physiopath Respir 15: 527–540, 1979.
- Mott JA, Friedman MS, Moorman JE, Ford E, Mannino DM, and Redd SC. The relationship between body mass index and the initial onset of asthma among children in the National Longitudinal Survey of Youth (Abstract). Am J Respir Crit Care Med 165: A435, 2002.
- National Center for Health Statistics. Health. United States, 2000. Growth Charts. Hyattsville, MD: Public Health Service. 2000.
- Ostro BD, Lipsett MJ, Mann JK, Braxton-Owens H, and White MC. Air pollution and asthma exacerbations among African-American children in Los Angeles. Inhal Toxicol 7:711–722, 1995.
- Paek D and McCool FD. Breathing patterns during varied activities. J Appl Physiol 73: 887–893, 1992.[Abstract/Free Full Text]
- Pope CA and Dockery DW. Acute health effects of PM10 pollution on symptomatic and asymptomatic children. Am Rev Respir Dis 145:1123–1128, 1992.[ISI][Medline]
- Schiller-Scotland CHF, Hlawa R, and Gebhart J. Total deposition of monodisperse aerosol particles in the respiratory tract of children. Toxicol Lett 72: 137–144, 1994.[CrossRef][ISI][Medline]
- Schwartz J, Dockery DW, Neas LM, Wypij D, Ware JH, Spengler JD, Koutrakis P, Speizer FE, and Ferris BG. Acute effects of summer air pollution on respiratory symptom reporting in children. Am J Respir Crit Care Med 150: 1234–1242, 1994.[Abstract]
- Smaldone GC and Messina MS. Flow limitation, cough, and patterns of aerosol deposition in humans. J Appl Physiol 59: 515–520, 1985.[Abstract/Free Full Text]
- Tabachnik E, Muller N, Toye B, and Levison H. Measurement of ventilation in children using the respiratory inductive plethysmograph. J Pediatr 99: 895–899, 1981.[CrossRef][ISI][Medline]
- Taulbee DB and Yu CP. A theory of aerosol deposition in the human respiratory tract. J Appl Physiol 38: 77–85, 1975.[Abstract/Free Full Text]
- Thurlbeck WM. Morphology of the aging lung. In: The Lung: Scientific Foundations, edited by Crystal RG and West JB. New York: Raven Press, 1991, vol. 2, p. 1743–1748.
- Tobin MJ, Chadha TS, Jenouri G, Birch SJ, Gazeroglu HB, and Sackner MA. Breathing patterns: 1. Normal subjects. Chest 84: 202–205, 1983.[Abstract/Free Full Text]
- Vedal S, Petkau J, White R, and Blair J. Acute effects of ambient inhalable particles in asthmatic and nonasthmatic children. Am J Respir Crit Care Med 157: 1034–1043, 1998.[Abstract/Free Full Text]
- Zeman KL and Bennett WD. Measuring alveolar dimensions at TLC by aerosol derived airspace morphometry. J Aerosol Med 8: 135–147, 1995.[ISI][Medline]
- Zeman KL, Scheuch G, Sommerer K, Brown JS, and Bennett WD. In vivo characterization of transitional bronchioles by aerosol-derived airway morphometry. J Appl Physiol 87: 920–927, 1999.[Abstract/Free Full Text]
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Copyright © 2004 by the American Physiological Society.
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ABSTRACT
METHODS
