Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data

Nikola Štefelová, Jan Dygrýn, Karel Hron, Aleš Gába, Lukáš Rubín and Javier Palarea-Albaladejo
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Nikola Štefelová: Faculty of Science, Palacký University Olomouc, 771 11 Olomouc, Czech Republic
Jan Dygrýn: Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic
Karel Hron: Faculty of Science, Palacký University Olomouc, 771 11 Olomouc, Czech Republic
Aleš Gába: Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic
Lukáš Rubín: Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic
Javier Palarea-Albaladejo: Biomathematics and Statistics Scotland, JCMB, The King’s Buildings, Edinburgh EH9 3FD, UK

IJERPH, 2018, vol. 15, issue 10, 1-18

Abstract: Although there is an increasing awareness of the suitability of using compositional data methodology in public health research, classical methods of statistical analysis have been primarily used so far. The present study aims to illustrate the potential of robust statistics to model movement behaviour using Czech adolescent data. We investigated: (1) the inter-relationship between various physical activity (PA) intensities, extended to model relationships by age; and (2) the associations between adolescents’ PA and sedentary behavior (SB) structure and obesity. These research questions were addressed using three different types of compositional regression analysis—compositional covariates, compositional response, and regression between compositional parts. Robust counterparts of classical regression methods were used to lessen the influence of possible outliers. We outlined the differences in both classical and robust methods of compositional data analysis. There was a pattern in Czech adolescents’ movement/non-movement behavior—extensive SB was related to higher amounts of light-intensity PA, and vigorous PA ratios formed the main source of potential aberrant observations; aging is associated with more SB and vigorous PA at the expense of light-intensity PA and moderate-intensity PA. The robust counterparts indicated that they might provide more stable estimates in the presence of outlying observations. The findings suggested that replacing time spent in SB with vigorous PA may be a powerful tool against adolescents’ obesity.

Keywords: compositional data; compositional linear regression; log-ratio methodology; pivot coordinates; physical activity (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:15:y:2018:i:10:p:2248-:d:175551

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