Elisabeth Winkler

Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06

AIMS Prolonged sedentary time is ubiquitous in developed economies and is associated with an adverse cardio-metabolic risk profile and premature mortality. This study examined the associations of objectively assessed sedentary time and breaks (interruptions) in sedentary time with continuous cardio-metabolic and inflammatory risk biomarkers, and whether these associations varied by sex, age, and/or race/ethnicity. METHODS AND RESULTS Cross-sectional analyses with 4757 participants (≥ 20 years) from the 2003/04 and 2005/06 US National Health and Nutrition Examination Survey (NHANES). An Actigraph accelerometer was used to derive sedentary time [< 100 counts per minute (cpm)] and breaks in sedentary time. Independent of potential confounders, including moderate-to-vigorous exercise, detrimental linear associations (P for trends < 0.05) of sedentary time with waist circumference, HDL-cholesterol, C-reactive protein, triglycerides, insulin, HOMA-%B, and HOMA-%S were observed. Independent of potential confounders and sedentary time, breaks were beneficially associated with waist circumference and C-reactive protein (P for trends <0.05). There was limited evidence of meaningful differences in associations with biomarkers by age, sex, or race/ethnicity. Notable exceptions were sex-differences in the associations of sedentary time and breaks with HDL-cholesterol, and race/ethnicity differences in the association of sedentary time with waist circumference with associations detrimental in non-Hispanic whites, null in Mexican Americans, and beneficial in non-Hispanic blacks. CONCLUSION These are the first population-representative findings on the deleterious associations of prolonged sedentary time with cardio-metabolic and inflammatory biomarkers. The findings suggest that clinical communications and preventive health messages on reducing and breaking up sedentary time may be beneficial for cardiovascular disease risk.

Measurement of adults' sedentary time in population-based studies.

Sedentary time (too much sitting) increasingly is being recognized as a distinct health risk behavior. This paper reviews the reliability and validity of self-reported and device-based sedentary time measures and provides recommendations for their use in population-based studies. The focus is on instruments that have been used in free-living, population-based research in adults. Data from the 2003-2006 National Health and Nutrition Examination Survey are utilized to compare the descriptive epidemiology of sedentary time that arises from the use of different sedentary time measures. A key recommendation from this review is that, wherever possible, population-based monitoring of sedentary time should incorporate both self-reported measures (to capture important domain- and behavior-specific sedentary time information) and device-based measures (to measure both total sedentary time and patterns of sedentary time accumulation).

Systematic review of maintenance of behavior change following physical activity and dietary interventions

OBJECTIVE In the past decade, there has been no systematic review of the evidence for maintenance of physical activity and/or dietary behavior change following intervention (follow-up). This systematic review addressed three questions: 1) How frequently do trials report on maintenance of behavior change? 2) How frequently do interventions achieve maintenance of behavior change? 3) What sample, methodologic, or intervention characteristics are common to trials achieving maintenance? DESIGN Systematic review of trials that evaluated a physical activity and/or dietary behavior change intervention among adults, with measurement at preintervention, postintervention, and at least 3 months following intervention completion (follow-up). MAIN OUTCOME MEASURES Maintenance of behavior change was defined as a significant between-groups difference at postintervention and at follow-up, for one or more physical activity and/or dietary outcome. RESULTS Maintenance outcomes were reported in 35% of the 157 intervention trials initially considered for review. Of the 29 trials that met all inclusion criteria, 21 (72%) achieved maintenance. Characteristics common to trials achieving maintenance included those related to sample characteristics (targeting women), study methods (higher attrition and pretrial behavioral screening), and intervention characteristics (longer duration [>24 weeks], face-to-face contact, use of more intervention strategies [>6], and use of follow-up prompts). CONCLUSIONS Maintenance of physical activity and dietary behavior change is not often reported; when it is, it is often achieved. To advance the evidence, the field needs consensus on reporting of maintenance outcomes, controlled evaluations of intervention strategies to promote maintenance, and more detailed reporting of interventions.

Prolonged sedentary time and physical activity in workplace and non-work contexts: a cross-sectional study of office, customer service and call centre employees

BackgroundTo examine sedentary time, prolonged sedentary bouts and physical activity in Australian employees from different workplace settings, within work and non-work contexts.MethodsA convenience sample of 193 employees working in offices (131), call centres (36) and customer service (26) was recruited. Actigraph GT1M accelerometers were used to derive percentages of time spent sedentary (<100 counts per minute; cpm), in prolonged sedentary bouts (≥20 minutes or ≥30 minutes), light-intensity activity (100–1951 cpm) and moderate-to-vigorous physical activity (MVPA; ≥1952 cpm). Using mixed models adjusted for confounders, these were compared for: work days versus non-work days; work hours versus non-work hours (work days only); and, across workplace settings.ResultsWorking hours were mostly spent sedentary (77.0%, 95%CI: 76.3, 77.6), with approximately half of this time accumulated in prolonged bouts of 20 minutes or more. There were significant (p<0.05) differences in all outcomes between workdays and non-work days, and, on workdays, between work- versus non-work hours. Results consistently showed “work” was more sedentary and had less light-intensity activity, than “non-work”. The period immediately after work appeared important for MVPA. There were significant (p<0.05) differences in all sedentary and activity outcomes occurring during work hours across the workplace settings. Call-centre workers were generally the most sedentary and least physically active at work; customer service workers were typically the least sedentary and the most active at work.ConclusionThe workplace is a key setting for prolonged sedentary time, especially for some occupational groups, and the potential health risk burden attached requires investigation. Future workplace regulations and health promotion initiatives for sedentary occupations to reduce prolonged sitting time should be considered.

Reallocating Time to Sleep, Sedentary Behaviors, or Active Behaviors: Associations With Cardiovascular Disease Risk Biomarkers, NHANES 2005–2006

Sleep and sedentary and active behaviors are linked to cardiovascular disease risk biomarkers, and across a 24-hour day, increasing time in 1 behavior requires decreasing time in another. We explored associations of reallocating time to sleep, sedentary behavior, or active behaviors with biomarkers. Data (n = 2,185 full sample; n = 923 fasting subanalyses) from the cross-sectional 2005-2006 US National Health and Nutrition Examination Survey were analyzed. The amounts of time spent in sedentary behavior, light-intensity activity, and moderate-to-vigorous physical activity (MVPA) were derived from ActiGraph accelerometry (ActiGraph LLC, Pensacola, Florida), and respondents reported their sleep duration. Isotemporal substitution modeling indicated that, independent of potential confounders and time spent in other activities, beneficial associations (P < 0.05) with cardiovascular disease risk biomarkers were associated with the reallocation of 30 minutes/day of sedentary time with equal time of either sleep (2.2% lower insulin and 2.0% lower homeostasis model assessment of β-cell function), light-intensity activity (1.9% lower triglycerides, 2.4% lower insulin, and 2.2% lower homeostasis model assessment of β-cell function), or MVPA (2.4% smaller waist circumference, 4.4% higher high-density lipoprotein cholesterol, 8.5% lower triglycerides, 1.7% lower glucose, 10.7% lower insulin, and 9.7% higher homeostasis model assessment of insulin sensitivity. These findings provide evidence that MVPA may be the most potent health-enhancing, time-dependent behavior, with additional benefit conferred from light-intensity activities and sleep duration when reallocated from sedentary time.

Light-Intensity Physical Activity and Cardiometabolic Biomarkers in US Adolescents

Background The minimal physical activity intensity that would confer health benefits among adolescents is unknown. The purpose of this study was to examine the associations of accelerometer-derived light-intensity (split into low and high) physical activity, and moderate- to vigorous-intensity physical activity with cardiometabolic biomarkers in a large population-based sample. Methods The study is based on 1,731 adolescents, aged 12–19 years from the 2003/04 and 2005/06 National Health and Nutrition Examination Survey. Low light-intensity activity (100–799 counts/min), high light-intensity activity (800 counts/min to <4 METs) and moderate- to vigorous-intensity activity (≥4 METs, Freedson age-specific equation) were accelerometer-derived. Cardiometabolic biomarkers, including waist circumference, systolic blood pressure, diastolic blood pressure, HDL-cholesterol, and C-reactive protein were measured. Triglycerides, LDL- cholesterol, insulin, glucose, and homeostatic model assessments of β-cell function (HOMA-%B) and insulin sensitivity (HOMA-%S) were also measured in a fasting sub-sample (n = 807). Results Adjusted for confounders, each additional hour/day of low light-intensity activity was associated with 0.59 (95% CI: 1.18–0.01) mmHG lower diastolic blood pressure. Each additional hour/day of high light-intensity activity was associated with 1.67 (2.94–0.39) mmHG lower diastolic blood pressure and 0.04 (0.001–0.07) mmol/L higher HDL-cholesterol. Each additional hour/day of moderate- to vigorous-intensity activity was associated with 3.54 (5.73–1.35) mmHG lower systolic blood pressure, 5.49 (1.11–9.77)% lower waist circumference, 25.87 (6.08–49.34)% lower insulin, and 16.18 (4.92–28.53)% higher HOMA-%S. Conclusions Time spent in low light-intensity physical activity and high light-intensity physical activity had some favorable associations with biomarkers. Consistent with current physical activity recommendations for adolescents, moderate- to vigorous-intensity activity had favorable associations with many cardiometabolic biomarkers. While increasing MVPA should still be a public health priority, further studies are needed to identify dose-response relationships for light-intensity activity thresholds to inform future recommendations and interventions for adolescents.

Associations of objectively-assessed physical activity and sedentary time with depression: NHANES (2005–2006)

BACKGROUND Studies provide conflicting evidence for the protective effects of moderate-to-vigorous-intensity physical activity on depression. Recent evidence suggests that sedentary behaviors may also be associated with depression. PURPOSE To examine the associations of accelerometer-derived moderate-to-vigorous-intensity physical activity and sedentary time with depression among a population-based sample. METHODS Cross-sectional study using 2,862 adults from the 2005-2006 US National Health and Nutrition Examination Survey. ActiGraph accelerometers were used to derive both moderate-to-vigorous-intensity physical activity and sedentary time. RESULTS Depression occurred in 6.8% of the sample. For moderate-to-vigorous-intensity physical activity, compared with those in quartile 1 (least active), significantly lower odds of depression were observed for those participants in quartiles 2 (OR=0.55, 95% CI, 0.34 to 0.89), 3 (OR=0.49, 95% CI, 0.26 to 0.93), and 4 (most active) (OR=0.37, 95% CI, 0.20 to 0.70) (p for trend p<0.01). In overweight/obese participants only, those in quartile 4 (most sedentary) had significantly higher odds for depression than those in quartile 1 (least sedentary) [quartile 3 vs 1 (OR=1.94, 95% CI, 1.01 to 3.68) and 4 vs 1 (OR=3.09, 95% CI, 1.25 to 7.68)]. CONCLUSION The current study identified lower odds of depression were associated with increasing moderate-to-vigorous-intensity physical activity and decreasing sedentary time, at least within overweight/obese adults.

Replacing sitting time with standing or stepping: associations with cardio-metabolic risk biomarkers

AIMS While excessive sitting time is related adversely to cardio-metabolic health, it is unknown whether standing is a suitable replacement activity or whether ambulatory movement is required. Using isotemporal substitution analyses, we modelled cross-sectional associations with cardio-metabolic risk biomarkers of reallocating time (2 h/day) from sitting to standing or to stepping. METHODS AND RESULTS A subsample of participants from the 2011/12 Australian Diabetes, Obesity, and Lifestyle Study wore the posture-based activPAL3 monitor [36-80 years (mean 57.9, SD 9.9 years); 57% women; n = 698 with data]. Associations of activPAL3-derived mean daily time sitting/lying (sitting), standing and stepping with body mass index (BMI), waist circumference, blood pressure, HbA1c, fasting glucose and lipids (high-density lipoprotein-, HDL, and low-density lipoprotein-cholesterol, total/HDL-cholesterol ratio, and triglycerides), and 2-h plasma glucose were examined. Adjusted for relevant confounders, sitting-to-standing reallocations were only significantly (P < 0.05) associated with approximately 2% lower fasting plasma glucose, 11% lower triglycerides, 6% lower total/HDL-cholesterol ratio, and 0.06 mmol/L higher HDL-cholesterol per 2 h/day. Sitting-to-stepping reallocations were only significantly associated with approximately 11% lower BMI, 7.5 cm lower waist circumference, 11% lower 2-h plasma glucose, 14% lower triglycerides, and 0.10 mmol/L higher HDL-cholesterol per 2 h/ day, while standing-to-stepping reallocations were only significantly associated with ∼10% lower BMI, 7 cm lower waist circumference, and 11% lower 2-h plasma glucose. CONCLUSION Findings suggested that sitting-reduction strategies targeting increased standing, stepping, or both, may benefit cardio-metabolic health. Standing is a simple alternative to sitting, and requires further examination in prospective and intervention studies.

Relationships of land use mix with walking for transport: do land uses and geographical scale matter?

Physical activity and public health recommendations now emphasize the creation of activity-friendly neighborhoods. Mixed land use in a neighborhood is important in this regard, as it reflects the availability of destinations to which residents can walk or ride bicycles, and thus is likely to contribute to residents’ active lifestyles that in turn will influence their overall health. Relationships between land use mix (LUM) and physical activity have not been apparent in some studies, which may be because geographical scale and the specificity of hypothesized environment–behavior associations are not taken into account. We compared the strength of association of four Geographic Information Systems-derived LUM measures with walking for transport and perceived proximity to destinations. We assessed physical activity behaviors of 2,506 adults in 154 Census Collection Districts (CCDs) in Adelaide, Australia, for which ‘‘original’’ LUM measures were calculated, and then refined by either: accounting for the geographic scale of measurement; including only the most-relevant land uses; or, both. The refined (but not the ‘‘original’’) LUM measures had significant associations with the frequency of walking for transport (p < 0.05) and area-corrected measures had significant associations with the duration of walking for transport. All LUM measures had significant associations with perceived proximity to destinations, but stronger associations were seen when using the refined measures compared with the original LUM. Identifying the LUM attributes most strongly associated with walking for transport is a priority and can inform environmental and policy initiatives that are needed to promote health-enhancing physical activity.

Measuring older adults' sedentary time: Reliability, validity, and responsiveness

PURPOSE With evidence that prolonged sitting has deleterious health consequences, decreasing sedentary time is a potentially important preventive health target. High-quality measures, particularly for use with older adults, who are the most sedentary population group, are needed to evaluate the effect of sedentary behavior interventions. We examined the reliability, validity, and responsiveness to change of a self-report sedentary behavior questionnaire that assessed time spent in behaviors common among older adults: watching television, computer use, reading, socializing, transport and hobbies, and a summary measure (total sedentary time). METHODS In the context of a sedentary behavior intervention, nonworking older adults (n = 48, age = 73 ± 8 yr (mean ± SD)) completed the questionnaire on three occasions during a 2-wk period (7 d between administrations) and wore an accelerometer (ActiGraph model GT1M) for two periods of 6 d. Test-retest reliability (for the individual items and the summary measure) and validity (self-reported total sedentary time compared with accelerometer-derived sedentary time) were assessed during the 1-wk preintervention period, using Spearman (ρ) correlations and 95% confidence intervals (CI). Responsiveness to change after the intervention was assessed using the responsiveness statistic (RS). RESULTS Test-retest reliability was excellent for television viewing time (ρ (95% CI) = 0.78 (0.63-0.89)), computer use (ρ (95% CI) = 0.90 (0.83-0.94)), and reading (ρ (95% CI) = 0.77 (0.62-0.86)); acceptable for hobbies (ρ (95% CI) = 0.61 (0.39-0.76)); and poor for socializing and transport (ρ < 0.45). Total sedentary time had acceptable test-retest reliability (ρ (95% CI) = 0.52 (0.27-0.70)) and validity (ρ (95% CI) = 0.30 (0.02-0.54)). Self-report total sedentary time was similarly responsive to change (RS = 0.47) as accelerometer-derived sedentary time (RS = 0.39). CONCLUSIONS The summary measure of total sedentary time has good repeatability and modest validity and is sufficiently responsive to change suggesting that it is suitable for use in interventions with older adults.