Walking and sitting in the Australian Antarctic Territory : mobility and imperial space

In 1995 and 1997, two major Australian expeditions travelled to Antarctica. They were the most heavily-reported Antarctican events of their two years: they were charged with the public production of Australian Antarctic spatiality. Both published exploration narratives: Don and Margie McIntyre’s Expedition Icebound generated an illustrated coffee-table book, Two Below Zero: A Year Alone in Antarctica, and the Spirit of Australia South Pole Expedition published its narrative as a video titled Walking on Ice: The History-Making Expedition to the South Pole. Yet, despite the fact that the two polar trips took place during the same period, their spatialities are markedly different. Walking on Ice is a mobile narrative of imperial exploration, while Two Below Zero is a static spatial story of colonial settlement. How polar mobility and relative immobility figure in Australia’s perceptions of, and claim to, nearly half of Antarctica is the focus of this chapter.

Correlates of sitting time in working age Australian women : who should be targeted with interventions to decrease sitting time?

Background: While there is emerging evidence that sedentary behavior is negatively associated with health risk, research on the correlates of sitting time in adults is scarce. Methods: Self-report data from 7,724 women born between 1973-1978 and 8,198 women born between 1946-1951 were collected as part of the Australian Longitudinal Study on Women’s Health. Linear regression models were computed to examine whether demographic, family and caring duties, time use, health and health behavior variables were associated with weekday sitting time. Results: Mean sitting time (SD) was 6.60 (3.32) hours/day for the 1973-1978 cohort and 5.70 (3.04) hours/day for the 1946-1951 cohort. Indicators of socio-economic advantage, such as full11 time work and skilled occupations in both cohorts and university education in the mid-age cohort, were associated with high sitting time. A cluster of ‘healthy behaviours’ was associated with lower sitting time in the mid-aged women (moderate/high physical activity levels, non-smoking, non-drinking). For both cohorts, sitting time was highest in women in full-time work, in skilled occupations and in those who spent the most time in passive leisure. Conclusions: The results suggest that, in young and mid-aged women, interventions for reducing sitting time should focus on both occupational and leisure-time sitting.

A qualitative study of older adults’ responses to sitting-time questions : do we get the information we want?

Background: In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults’ understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE). Methods: Australian community-dwelling adults aged 65+ years answered the IPAQ and PASE sitting questions in face-to-face semi-structured interviews. IPAQ uses one open-ended question to assess sitting on a weekday in the last 7 days 'at work, at home, while doing coursework and during leisure time'; PASE uses a three-part closed question about daily leisure-time sitting in the last 7 days. Participants expressed their thoughts out loud while answering each question. They were then probed about their responses. Interviews were recorded, transcribed and coded into themes. Results: Mean age of the 28 male and 27 female participants was 73 years (range 65-89). The most frequently reported activity was watching TV. For both questionnaires, many participants had difficulties understanding what activities to report. Some had difficulty understanding what activities should be classified as ‘leisure-time sitting’. Some assumed they were being asked to only report activities provided as examples. Most reported activities they normally do, rather than those performed on a day in the previous week. Participants used a variety of strategies to select ‘a day’ for which they reported their sitting activities and to calculate sitting time on that day. Therefore, many different ways of estimating sitting time were used. Participants had particular difficulty reporting their daily sitting-time when their schedules were not consistent across days. Some participants declared the IPAQ sitting question too difficult to answer. Conclusion: The accuracy of older adults’ self-reported sitting time is questionable given the challenges they have in answering sitting-time questions. Their responses to sitting-time questions may be more accurate if our recommendations for clarifying the sitting domains, providing examples relevant to older adults and suggesting strategies for formulating responses are incorporated. Future quantitative studies should include objective criterion measures to assess validity and reliability of these questions.

Physical activity, sitting and depression during pregnancy

Aims The aim of this cross sectional study is to explore levels of physical activity and sitting behaviour amongst a sample of pregnant Australian women (n = 81), and investigate whether reported levels of physical activity and/or time spent sitting were associated with depressive symptom scores after controlling for potential covariates. Methods Study participants were women who attended the antenatal clinic of a large Brisbane maternity hospital between October and November 2006. Data relating to participants. current levels of physical activity, sitting behaviour, depressive symptoms, demographic characteristics and exposure to known risk factors for depression during pregnancy were collected; via on-site survey, follow-up telephone interview (approximately one week later) and post delivery access to participant hospital records. Results Participants were aged 29.5 (¡¾ 5.6) years and mostly partnered (86.4%) with a gross household income above $26,000 per annum (88.9%). Levels of physical activity were generally low, with only 28.4 % of participants reporting sufficient total activity and 16% of participants reporting sufficient planned (leisure-time) activity. The sample mean for depressive symptom scores measured by the Hospital Anxiety and Depression Scale (HADS-D) was 6.38 (¡¾ 2.55). The mean depressive symptom scores for participants who reported total moderate-to-vigorous activity levels of sufficient, insufficient, and none, were 5.43 (¡¾ 1.56), 5.82 (¡¾ 1.77) and 7.63 (¡¾ 3.25), respectively. Hierarchical multivariable linear regression modelling indicated that after controlling for covariates, a statistically significant difference of 1.09 points was observed between mean depressive symptom scores of participants who reported sufficient total physical activity, compared with participants who reported they were engaging in no moderate-to-vigorous activity in a typical week (p = 0.05) but this did not reach the criteria for a clinically meaningful difference. Total physical activity was contributed 2.2% to the total 30.3% of explained variance within this model. The other main contributors to explained variance in multivariable regression models were anxiety symptom scores and the number of existing children. Further, a trend was observed between higher levels of planned sitting behaviour and higher depressive symptom scores (p = 0.06); this correlation was not clinically meaningful. Planned sitting contributed 3.2% to the total 31.3 % of explained variance. The number of regression covariates and limited sample size led to a less than ideal ratio of covariates to participants, probably attenuating this relationship. Specific information about the sitting-based activities in which participants engaged may have provided greater insight about the relationship between planned sitting and depressive symptoms, but these data were not captured by the present study. Conclusions The finding that higher levels of physical activity were associated with lower levels of depressive symptoms is consistent with the current body of existing literature in pregnant women, and with a larger body of evidence based in general population samples. Although this result was not considered clinically meaningful, the criterion for a clinically meaningful result was an a priori decision based on quality of life literature in non-pregnant populations and may not truly reflect a difference in symptoms that is meaningful to pregnant women. Further investigation to establish clinically meaningful criteria for continuous depressive symptom data in pregnant women is required. This result may have implications relating to prevention and management options for depression during pregnancy. The observed trend between planned sitting and depressive symptom scores is consistent with literature based on leisure-time sitting behaviour in general population samples, and suggests that further research in this area, with larger samples of pregnant women and more specific sitting data is required to explore potential associations between activities such as television viewing and depressive symptoms, as this may be an area of behaviour that is amenable to modification.

Sit versus stand : can sitting be accurately identified using MTI accelerometer data?

High levels of sitting have been linked with poor health outcomes. Previously a pragmatic MTI accelerometer data cut-point (100 count/min-1) has been used to estimate sitting. Data on the accuracy of this cut-point is unavailable. PURPOSE: To ascertain whether the 100 count/min-1 cut-point accurately isolates sitting from standing activities. METHODS: Participants fitted with an MTI accelerometer were observed performing a range of sitting, standing, light & moderate activities. 1-min epoch MTI data were matched to observed activities, then re-categorized as either sitting or not using the 100 count/min-1 cut-point. Self-report demographics and current physical activity were collected. Generalized estimating equation for repeated measures with a binary logistic model analyses (GEE), corrected for age, gender and BMI, were conducted to ascertain the odds of the MTI data being misclassified. RESULTS: Data were from 26 healthy subjects (8 men; 50% aged <25 years; mean BMI (SD) 22.7(3.8)m/kg2). MTI sitting and standing data mode was 0 count/min-1, with 46% of sitting activities and 21% of standing activities recording 0 count/min-1. The GEE was unable to accurately isolate sitting from standing activities using the 100 count/min-1 cut-point, since all sitting activities were incorrectly predicted as standing (p=0.05). To further explore the sensitivity of MTI data to delineate sitting from standing, the upper 95% confidence interval of the mean for the sitting activities (46 count/min-1) was used to re-categorise the data; this resulted in the GEE correctly classifying 49% of sitting, and 69% of standing activities. Using the 100 count/min-1 cut-point the data were re-categorised into a combined ‘sit/stand’ category and tested against other light activities: 88% of sit/stand and 87% of light activities were accurately predicted. Using Freedson’s moderate cut-point of 1952 count/min-1 the GEE accurately predicted 97% of light vs. 90% of moderate activities. CONCLUSION: The distributions of MTI recorded sitting and standing data overlap considerably, as such the 100 count/min -1 cut-point did not accurately isolate sitting from other static standing activities. The 100 count/min -1 cut-point more accurately predicted sit/stand vs. other movement orientated activities.

Which older women could benefit from interventions to decrease sitting time and increase physical activity?

In addition to the well-known health risks associated with lack of physical activity (PA), evidence is emerging about the health risks of sedentary behaviour (sitting). Research about patterns and correlates of sitting and PA in older women is scarce. METHODS: Self-report data from 6,116 women aged 76-81 years were collected as part of the Australian Longitudinal Study on Woman’s Health. Linear regression models were computed to examine whether demographic, social and health factors were associated with sitting and PA. RESULTS: Women who did no PA sat more than women who did any PA (p<0.001). Seven correlates were associated with sitting and PA (p<0.05). Five of these were associated with more sitting and less PA: three health-related (BMI, chronic conditions, anxiety/depression) and two social correlates (caring duties, volunteering). One demographic (being from another English-speaking country) and one social correlate (more social interaction) were associated with more sitting and more PA. Four correlates, two demographic (living in a city; post-high school education), one social (being single), and one health-related correlate (dizziness/loss of balance) were associated with more sitting only. Two other health-related correlates (stiff/painful joints; feet problems) were associated with less PA only. CONCLUSION: Sedentary behaviour and PA are distinct behaviours in older Australian women. Information about the correlates of both behaviours can be used to identify population groups who might benefit from interventions to reduce sedentary behaviour and/or increase PA.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

ActiGraph GT3X determined variations in “free-living” standing, lying, and sitting duration among sedentary adults

Background Overweight and obesity has become a serious public health problem in many parts of the world. Studies suggest that making small changes in daily activity levels such as “breaking-up” sedentary time (i.e., standing) may help mitigate the health risks of sedentary behavior. The aim of the present study was to examine time spent in standing (determined by count threshold), lying, and sitting postures (determined by inclinometer function) via the ActiGraph GT3X among sedentary adults with differing weight status based on body mass index (BMI) categories. Methods Participants included 22 sedentary adults (14 men, 8 women; mean age 26.5 ± 4.1 years). All subjects completed the self-report International Physical Activity Questionnaire to determine time spent sitting over the previous 7 days. Participants were included if they spent seven or more hours sitting per day. Postures were determined with the ActiGraph GT3X inclinometer function. Participants were instructed to wear the accelerometer for 7 consecutive days (24 h a day). BMI was categorized as: 18.5 to <25 kg/m2 as normal, 25 to <30 kg/m2 as overweight, and ≥30 kg/m2 as obese. Results Participants in the normal weight (n = 10) and overweight (n = 6) groups spent significantly more time standing (after adjustment for moderate-to-vigorous intensity physical activity and wear-time) (6.7 h and 7.3 h respectively) and less time sitting (7.1 h and 6.9 h respectively) than those in obese (n = 6) categories (5.5 h and 8.0 h respectively) after adjustment for wear-time (p < 0.001). There were no significant differences in standing and sitting time between normal weight and overweight groups (p = 0.051 and p = 0.670 respectively). Differences were not significant among groups for lying time (p = 0.55). Conclusion This study described postural allocations standing, lying, and sitting among normal weight, overweight, and obese sedentary adults. The results provide additional evidence for the use of increasing standing time in obesity prevention strategies.

Sitting-time, physical activity and depressive symptoms in mid-aged women

Background: Associations between sitting-time and physical activity (PA) with depression are unclear. Purpose: To examine concurrent and prospective associations between both sitting-time and PA with prevalent depressive symptoms in mid-aged Australian women. Methods: Data were from 8,950 women, aged 50-55 years in 2001, who completed mail surveys in 2001, 2004, 2007 and 2010. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression questionnaire. Associations between sitting-time (≤4, >4-7, >7 hrs/day) and PA (none, some, meeting guidelines) with depressive symptoms (symptoms/no symptoms) were examined in 2011 in concurrent and lagged mixed effect logistic modeling. Both main effects and interaction models were developed. Results: In main effects modeling, women who sat >7 hrs/day (OR 1.47, 95%CI 1.29-1.67) and women who did no PA (OR 1.99, 95%CI 1.75-2.27) were more likely to have depressive symptoms than women who sat ≤4 hrs/day and who met PA guidelines, respectively. In interaction modeling, the likelihood of depressive symptoms in women who sat >7 hrs/day and did no PA was triple that of women who sat ≤4 hrs/day and met PA guidelines (OR 2.96, 95%CI 2.37-3.69). In prospective main effects and interaction modeling, sitting-time was not associated with depressive symptoms, but women who did no PA were more likely than those who met PA guidelines to have future depressive symptoms (OR 1.26, 95%CI 1.08-1.47). Conclusions: Increasing PA to a level commensurate with PA guidelines can alleviate current depression symptoms and prevent future symptoms in mid-aged women. Reducing sitting-time may ameliorate current symptoms.

Depressive symptoms during pregnancy: Exploring the role of sitting

Statement of problem: Studies exploring relationships between sitting and mental health have been conducted in child and adult, but not pregnant populations. Depression during pregnancy is associated with deleterious outcomes for mothers and children, and shortcomings have been identified in current management strategies. Modifiable lifestyle behaviors may provide more acceptable alternatives to current management strategies if shown to be important. The aim of this study was to explore the relationship between sitting behavior and depressive symptoms in a population of pregnant Australian women. Methods: This pilot cross-sectional study included 81 pregnant women in Brisbane, Australia. Depressive symptoms were measured using the Hospital Anxiety and Depression Scale (HADS). Sitting behavior was measured using the Australian Women's Activity Survey (AWAS). Several potential covariates were also assessed. Linear regression analyses were used to explore the relationship between sitting and depressive symptoms, whilst controlling for known covariates. Results: The model investigating “total sitting time” showed no association with depressive symptoms (F = .77, p = 0.38). The model investigating “planned leisure sitting time” was statistically significant (F = 4.42, p = 0.04): significant contributors to the model variance were HADS anxiety score (p = 0.003) and number of existing children (p = 0.02). “Planned leisure sitting time” showed a statistical trend toward significance (p = 0.06). Conclusions: This study suggests further investigation of the relationship between sitting, particularly planned leisure sitting, and depression during pregnancy is warranted. Future research should include a larger sample and an objective measure of leisure time sitting.

Intervening to reduce workplace sitting time : how and when do changes to sitting time occur?

Objective To investigate how and when changes in workplace sitting time occurred following a workplace intervention to inform evaluation of intervention success. Method The 4-week Stand Up Comcare study (June–September 2011) aimed to reduce workplace sitting time via regularly interrupting and replacing sitting time throughout the day. Activity monitor (activPAL3) workplace data from control (n=22) and intervention participants (n=21) were analysed. Differences in the number and usual duration of sitting bouts were used to evaluate how change occurred. To examine when change occurred, intervention effects were compared by hour since starting work and hour of the workday. Change in workplace activity (sitting, standing, stepping) was examined to further inform alignment with intervention messages. Individual variability was examined in how and when the change occurred. Results Overall, behavioural changes aligned with intervention aims. All intervention participants reduced total workplace sitting time, though there was wide individual variability observed (range −29 to −262 min per 8 h workday). On average, intervention participants reduced number of sitting bouts (−4.6 bouts (95% CI −10.1 to 1.0), p=0.106) and usual sitting bout duration (−5.6 min (95% CI −9.8 to −1.4, p=0.011)) relative to controls. Sitting time reductions were observed across the workday, though intervention effects varied by hour of the day (p=0.015). The intervention group successfully adopted the Stand Up and Sit Less intervention messages across the day. Conclusion These analyses confirmed that this workplace intervention successfully modified sitting behaviour as intended (ie, fewer and shorter sitting bouts, with changes occurring throughout the day).

Mid-Aged Adults' Sitting Time in Three Contexts

BACKGROUND: To develop evidence-based approaches for reducing sedentary behavior, there is a need to identify the specific settings where prolonged sitting occurs, associated factors, and variations. PURPOSE: To examine the sociodemographic and health factors associated with mid-aged adults' sitting time in three contexts and variations between weekdays and weekend days. METHODS: A mail survey was sent to 17,000 adults (aged 40-65 years) in 2007; 11,037 responses were received (68.5%); and 7719 were analyzed in 2010. Respondents indicated time spent sitting on a usual weekday and weekend day for watching TV, general leisure, and home computer use. Multivariate linear mixed models with area-level random intercepts were used to examine (1) associations between sociodemographic and health variables and sitting time, and (2) interaction effects of weekday/weekend day with each of gender, age, education, and employment status, on sitting time. RESULTS: For each context, longer sitting times were reported by those single and living alone, and those whose health restricted activity. For watching TV, longer sitting times were reported by men; smokers; and those with high school or lower education, not in paid employment, in poor health, and with BMI ≥25. For general leisure, longer sitting times were reported by women, smokers, and those not employed full-time. For home computer use, longer sitting times were reported by men; and those aged 40-44 years, with university qualifications; in the mid-income range; and with BMI ≥30. Sitting times tended to be longer on weekend days than weekdays, although the extent of this differed among sociodemographic groups. CONCLUSIONS: Sociodemographic and health factors associated with sitting time differ by context and between weekdays and weekend days.