Self-reported domain-specific and accelerometer-based physical activity and sedentary behaviour in relation to psychological distress among an urban Asian population

Abstract Background The interpretation of previous studies on the association of physical activity and sedentary behaviour with psychological health is limited by the use of mostly self-reported physical activity and sedentary behaviour, and a focus on Western populations. We aimed to explore the association of self-reported and devise-based measures of physical activity and sedentary behaviour domains on psychological distress in an urban multi-ethnic Asian population. Methods From a population-based cross-sectional study of adults aged 18–79 years, data were used from an overall sample (n = 2653) with complete self-reported total physical activity/sedentary behaviour and domain-specific physical activity data, and a subsample (n = 703) with self-reported domain-specific sedentary behaviour and accelerometry data. Physical activity and sedentary behaviour data were collected using the Global Physical Activity Questionnaire (GPAQ), a domain-specific sedentary behaviour questionnaire and accelerometers. The Kessler Screening Scale (K6) and General Health Questionnaire (GHQ-12) were used to assess psychological distress. Logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals, adjusted for socio-demographic and lifestyle characteristics. Results The sample comprised 45.0% men (median age = 45.0 years). The prevalence of psychological distress based on the K6 and GHQ-12 was 8.4% and 21.7%, respectively. In the adjusted model, higher levels of self-reported moderate-to-vigorous physical activity (MVPA) were associated with significantly higher odds for K6 (OR = 1.47 [1.03–2.10]; p-trend = 0.03) but not GHQ-12 (OR = 0.97 [0.77–1.23]; p-trend = 0.79), when comparing the highest with the lowest tertile. Accelerometry-assessed MVPA was not significantly associated with K6 (p-trend = 0.50) nor GHQ-12 (p-trend = 0.74). The highest tertile of leisure-time physical activity, but not work- or transport-domain activity, was associated with less psychological distress using K6 (OR = 0.65 [0.43–0.97]; p-trend = 0.02) and GHQ-12 (OR = 0.72 [0.55–0.93]; p-trend = 0.01). Self-reported sedentary behaviour was not associated with K6 (p-trend = 0.90) and GHQ-12 (p-trend = 0.33). The highest tertile of accelerometry-assessed sedentary behaviour was associated with significantly higher odds for K6 (OR = 1.93 [1.00–3.75]; p-trend = 0.04), but not GHQ-12 (OR = 1.34 [0.86–2.08]; p-trend = 0.18). Conclusions Higher levels of leisure-time physical activity and lower levels of accelerometer-based sedentary behaviour were associated with lower psychological distress. This study underscores the importance of assessing accelerometer-based and domain-specific activity in relation to mental health, instead of solely focusing on total volume of activity

Predicting walking METs and energy expenditure from speed or accelerometry

PURPOSE: a) Compare the predictive potential of speed and CSA(hip) (Computer Science Applications accelerometer positioned on the hip) for level terrain walking METs (1 MET = VO2 of 3.5 mL.kg(-1).min(-1)) and energy expenditure (kcal.min(-1)); b) cross-validate previously published CSA(hip)- and speed-based MET and energy expenditure prediction equations; c) measure self-paced walking speed, exercise intensity (METs) and energy expenditure in the middle aged population. METHODS: Seventy-two 35- to 45-yr-old volunteers walked around a level, paved quadrangle at what they perceived to be a moderate pace. Oxygen consumption was measured using the criterion Douglas bag technique. Speed, CSA(hip), heart rate, and Borg rating of perceived exertion were also monitored. RESULTS: Speed explained 10% more variance of walking METs than CSA(hip). Speed and mass explained 8% more variance of walking energy expenditure (kcal.min) than CSA(hip) and mass. The best previously published regression equations predict our walking METs and energy expenditures within 95% prediction limits of +/- 0.7 METs and +/- 1.0 kcal.min(-1), respectively. Women paced themselves at a significantly higher mean speed (5.5 km.h(-1)) and intensity (4.1 METs) than their male counterparts (5.2 km.h(-1) and 3.8 METs). Both genders expended approximately 0.75 kcal.kg(-1) for every kilometer of level terrain walked. CONCLUSION: Speed-based MET and energy expenditure predictions during level terrain walking were more accurate than those utilizing CSA(hip).Brooks, Anthony G.; Gunn, Simon M.; Withers, Robert T.; Gore, Christopher J. and Plummer, John L.http://www.ncbi.nlm.nih.gov/pubmed/1601514

Conducting accelerometer-based activity assessments in field-based research

Purpose The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. Methods We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. Results No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3–5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. Conclusion Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance

Assessment of Differing Definitions of Accelerometer Nonwear Time

Measuring physical activity with objective tools, such as accelerometers, is becoming more common. Accelerometers measure acceleration multiple times within a given frequency and summarize this as a count over a pre-specified time period or epoch. The resultant count represents acceleration over the epoch length. Accelerometers eliminate biases associated with self-reporting measures of physical activity. With the increasingly widespread use of accelerometers, standardization of how the data are collected and reported across studies is needed. In 2005, Masse and colleagues identified five methodological issues regarding reducing accelerometer data to derive summary measures: (1) identifying accelerometer wearing time; (2) defining minimal wear time for a valid day; (3) identifying spurious data; (4) computing summary variables and aggregating days of data; and (5) extracting bouts of activity. This study focuses on the first issue; specifically, identifying nonwearing time of th