Different conceptual constructs for modelling sedentary behaviour and physical activity: the impact on the correlates of behaviour

Abstract

BackgroundResearch on the correlates of physical activity (PA) and sedentary behaviour (SB) to date has used independent prediction equations for each behaviour, without considering that they are both part of the same continuum of movement. This assumption of independence might lead to inaccurate estimates because common underlying latent variables may simultaneously influence the propensity to engage in PA and SB. This study tests empirically the interdependent nature of PA and SB by comparing independent equations (current approach in the literature), and joint estimators (a novel but unexplored approach). Using Health Survey for England 2008 data, accelerometry-accessed PA and SB were separately modelled (using ordinary least squared regressions - OLS) and then jointly (using seemingly unrelated regressions -SUR). We tested for diagonality, specification, and goodness of fit.FindingsThe best fit models were the ones that allowed for interdependence of the two movement-related behaviours (rho = −0.156; p < 0.001). The SUR showed more favourable properties compared to OLS models; producing lower standard errors and more consistent and efficient coefficients. The efficiency gain was more pronounced in the SB equation (Chi2 = 92.75; p < 0.001).ConclusionEvidence from a large national population-wide accelerometry study suggests that accounting for the interdependent nature of PA and SB in prediction equations leads to more efficient modelling estimates. Further research using different samples is, however, required to fully understand the magnitude of efficiency gains accruable from using the joint estimators.

Low level of physical activity and sedentary behaviour in elderly: a systematic review of the parameters

“…Several studies were considered, which presented various definitions for sedentary behavior and/or low levels of physical activity. Different methods of characterizing sedentary behavior included reporting sitting activities more than four hours a day more than five days a week 32 , classifying as inactive accordingly prompt cards, counting per minute (<100 CPM) for sedentary behavior equivalent to <1.5 Metabolic Equivalent of Task (MET) 33 , number of sedentary bouts equivalent to <100 CPM counted through accelerometer and the number of daily minutes with a minutely accelerometer count of <200 counts/minute 27 . The characterization of low levels of physical activity included reporting how often they took part of a vigorous-intensity physical activity, moderate intensity and low intensity through prompt cards with different pictures of the activities to help 31 , classifying physical activity at light activity (1.5-3.0 MET) and moderate to vigorous physical activity (≥3 MET) 33 , calculating to vigorous physical activity bouts of at least 10 minutes 33 .…”

“…In this sense, this lack of standardization resulted in several outcomes related to sedentary behavior and level of physical activity. For example, Smith et al 29 found, after investigate physical activity during 10 years, that age was associated with a lower likelihood of being physically active and physical activity levels decreased over time 29 whereas another study verified that aging was associated to lower levels of moderate to vigorous physical activity 27 . However, while the former study used prompt cards to help individuals to self-report physical activity levels, second classified subjects in sedentary or having low level of physical activity using an accelerometer.…”

“…Additionally, the distinct instruments used in the investigations are another point to be considered. Direct measurement instruments (accelerometer and pedometer) used in some of the studies [26][27][28][29] give a more reliable measure about sedentary behavior patterns than indirect measurement instruments (questionnaire and self-reports) although the second are more viable to apply in larger studies [30][31][32] .…”

“…Box 2 summarizes the descriptions about the studies definition of sedentarybehavior or physical activity, to teach change behavior, different strategies were used in the definition variable was referred the amount, duration, intensity and/or type for physical activity. 27 SB defined as the number of daily minutes with a minutely accelerometer count of <200 counts/minute. MVPA was defined as a minutely count of ≥2020 counts/minute Blodgett et al 28 SB defined as 0-100 counts/min on the ActiGraph Accelerometer.…”

“…In addition, conversely to physical activity, sedentary behavior is associated to several poor health indexes in elderly people (high blood pressure, obesity and high levels of blood glucose) 24,25 . However, differently from physical activity, studies investigating sedentary behavior or low levels of physical activity in this population have adopted several and different parameters to determine their concepts, including direct measures from electronic devices (accelerometer and pedometers) [26][27][28][29] and indirect from self-report questionnaires and diaries [30][31][32] , which in turnvarybetween reporting sitting activities more than four hours a day more than five days a weekand daily activities equivalent to <1.5 Metabolic Equivalent of Task (MET) 33 . Thus, this lack of standardization between sedentary behavior concepts adopted in the several studies makes hard to establish parameters to compare the reports about this issue.…”