TY - JOUR
T1 - A novel method for quantifying the inhaled dose of air pollutants based on heart rate, breathing rate and forced vital capacity
AU - Greenwald, Roby
AU - Hayat, Matthew J.
AU - Barton, Jerusha
AU - Lopukhin, Anastasia
N1 - Publisher Copyright:
© 2016 Greenwald et al.
PY - 2016/1
Y1 - 2016/1
N2 - To better understand the interaction of physical activity and air pollution exposure, it is important to quantify the change in ventilation rate incurred by activity. In this paper, we describe a method for estimating ventilation using easily-measured variables such as heart rate (HR), breathing rate (fB), and forced vital capacity (FVC). We recruited healthy adolescents to use a treadmill while we continuously measured HR, fB, and the tidal volume (VT) of each breath. Participants began at rest then walked and ran at increasing speed until HR was 160-180 beats per minute followed by a cool down period. The novel feature of this method is that minute ventilation (V˙E) was normalized by FVC. We used general linear mixed models with a random effect for subject and identified nine potential predictor variables that influence either V˙E or FVC. We assessed predictive performance with a five-fold cross-validation procedure. We used a brute force selection process to identify the best performing models based on cross-validation percent error, the Akaike Information Criterion and the p-value of parameter estimates. We found a two-predictor model including HR and fB to have the best predictive performance (V˙E/FVC = -4.247+0.0595HR+0.226fB, mean percent error = 8.1±29%); however, given the ubiquity of HR measurements, a one-predictor model including HR may also be useful (V˙E/FVC = -3.859+0.101HR, mean percent error = 11.3±36%).
AB - To better understand the interaction of physical activity and air pollution exposure, it is important to quantify the change in ventilation rate incurred by activity. In this paper, we describe a method for estimating ventilation using easily-measured variables such as heart rate (HR), breathing rate (fB), and forced vital capacity (FVC). We recruited healthy adolescents to use a treadmill while we continuously measured HR, fB, and the tidal volume (VT) of each breath. Participants began at rest then walked and ran at increasing speed until HR was 160-180 beats per minute followed by a cool down period. The novel feature of this method is that minute ventilation (V˙E) was normalized by FVC. We used general linear mixed models with a random effect for subject and identified nine potential predictor variables that influence either V˙E or FVC. We assessed predictive performance with a five-fold cross-validation procedure. We used a brute force selection process to identify the best performing models based on cross-validation percent error, the Akaike Information Criterion and the p-value of parameter estimates. We found a two-predictor model including HR and fB to have the best predictive performance (V˙E/FVC = -4.247+0.0595HR+0.226fB, mean percent error = 8.1±29%); however, given the ubiquity of HR measurements, a one-predictor model including HR may also be useful (V˙E/FVC = -3.859+0.101HR, mean percent error = 11.3±36%).
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U2 - 10.1371/journal.pone.0147578
DO - 10.1371/journal.pone.0147578
M3 - Article
C2 - 26809066
AN - SCOPUS:85013127374
SN - 1932-6203
VL - 11
JO - PloS one
JF - PloS one
IS - 1
M1 - e0147578
ER -