TY - JOUR
T1 - Factors most strongly associated with breathlessness in a population aged 50–64 years
AU - Olsson, Max
AU - Björkelund, Anders j
AU - Sandberg, Jacob
AU - Blomberg, Anders
AU - Börjesson, Mats
AU - Currow, David
AU - Malinovschi, Andrei
AU - Sköld, Magnus
AU - Wollmer, Per
AU - Torén, Kjell
AU - Östgren, Carl johan
AU - Engström, Gunnar
AU - Ekström, Magnus
PY - 2024
Y1 - 2024
N2 - Background: Breathlessness is a troublesome and prevalent symptom in the population, but knowledge of related factors is scarce. The aim of this study was to identify the factors most strongly associated with breathlessness in the general population and to describe the shapes of the associations between the main factors and breathlessness.Methods: a cross-sectional analysis of the multicentre population-based SwedishCArdioPulmonary bioImage Study (SCAPIS) of adults aged 50 to 64 years. Breathlessness was defined as a modified Medical Research Council (mMRC) breathlessness rating ≥2. The machine-learning algorithm extreme gradient boosting (XGBoost) was used to classify participants as either breathless or nonbreathless using 449 factors, including physiological measurements, blood samples, computer tomography cardiac and lung measurements, lifestyle, health conditions, and socioeconomics. The strength of the associations between thefactors and breathlessness were measured by SHapley Additive exPlanations (SHAP), with higher scores reflecting stronger associations.Results: A total of 28,730 participants (52% women) were included in the study. The strongest associated factors for breathlessness were (in order of magnitude): body mass index (BMI; [SHAP score] 0.39), forced expiratory volume in 1 second (FEV1; 0.32), physical activity measured by accelerometery (0.27), sleep apnoea (0.22), diffusing lung capacity for carbon monoxide (0.21), self-reported physical activity (0.17), chest pain when hurrying (0.17), high-sensitivity C-reactive protein (hs-CRP) (0.17), recent weight change (0.14), and cough (0.13).Conclusion: This large population-based study of men and women aged 50 - 64 years identified the main factors related to breathlessness that may be prevented or amenable to public health interventions.
AB - Background: Breathlessness is a troublesome and prevalent symptom in the population, but knowledge of related factors is scarce. The aim of this study was to identify the factors most strongly associated with breathlessness in the general population and to describe the shapes of the associations between the main factors and breathlessness.Methods: a cross-sectional analysis of the multicentre population-based SwedishCArdioPulmonary bioImage Study (SCAPIS) of adults aged 50 to 64 years. Breathlessness was defined as a modified Medical Research Council (mMRC) breathlessness rating ≥2. The machine-learning algorithm extreme gradient boosting (XGBoost) was used to classify participants as either breathless or nonbreathless using 449 factors, including physiological measurements, blood samples, computer tomography cardiac and lung measurements, lifestyle, health conditions, and socioeconomics. The strength of the associations between thefactors and breathlessness were measured by SHapley Additive exPlanations (SHAP), with higher scores reflecting stronger associations.Results: A total of 28,730 participants (52% women) were included in the study. The strongest associated factors for breathlessness were (in order of magnitude): body mass index (BMI; [SHAP score] 0.39), forced expiratory volume in 1 second (FEV1; 0.32), physical activity measured by accelerometery (0.27), sleep apnoea (0.22), diffusing lung capacity for carbon monoxide (0.21), self-reported physical activity (0.17), chest pain when hurrying (0.17), high-sensitivity C-reactive protein (hs-CRP) (0.17), recent weight change (0.14), and cough (0.13).Conclusion: This large population-based study of men and women aged 50 - 64 years identified the main factors related to breathlessness that may be prevented or amenable to public health interventions.
KW - breathlessness
KW - dyspnea
KW - factors
KW - machine learning
U2 - 10.1183/23120541.00582-2023
DO - 10.1183/23120541.00582-2023
M3 - Article
C2 - 38529345
SN - 2312-0541
VL - 10
JO - ERJ open research
JF - ERJ open research
IS - 2
M1 - 00582-2023
ER -