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. Author manuscript; available in PMC: 2022 May 4.
Published in final edited form as: J Aging Phys Act. 2020 Jun 4;28(6):864–874. doi: 10.1123/japa.2019-0470

Reducing Sitting Time in Obese Older Adults: The I-STAND Randomized Controlled Trial

Dori E Rosenberg 1, Melissa L Anderson 2, Anne Renz 3, Theresa E Matson 4, Amy K Lee 5, Mikael Anne Greenwood-Hickman 6, David E Arterburn 7, Paul A Gardiner 8, Jacqueline Kerr 9, Jennifer B McClure 10
PMCID: PMC9067913  NIHMSID: NIHMS1798986  PMID: 32498040

Abstract

Background:

The authors tested the efficacy of the “I-STAND” intervention for reducing sitting time, a novel and potentially health-promoting approach, in older adults with obesity.

Methods:

The authors recruited 60 people (mean age = 68 ± 4.9 years, 68% female, 86% White; mean body mass index = 35.4). The participants were randomized to receive the I-STAND sitting reduction intervention (n = 29) or healthy living control group (n = 31) for 12 weeks. At baseline and at 12 weeks, the participants wore activPAL devices to assess sitting time (primary outcome). Secondary outcomes included fasting glucose, blood pressure, and weight. Linear regression models assessed between-group differences in the outcomes.

Results:

The I-STAND participants significantly reduced their sitting time compared with the controls (−58 min per day; 95% confidence interval [−100.3, −15.6]; p = .007). There were no statistically significant changes in the secondary outcomes.

Conclusion:

I-STAND was efficacious in reducing sitting time, but not in changing health outcomes in older adults with obesity.

Keywords: cardiovascular health, obesity, sedentary behavior

Currently, about 40% of U.S. adults aged 65–74 years have obesity (Fakhouri, Ogden, Carroll, Kit, & Flegal, 2012). This number is likely to rise as the U.S. population of adults over the age of 60 grows to become 25% of the population (Federal Interagency Forum on Aging-Related Statistics, 2012). Obesity is strongly associated with elevated cardiovascular disease, hypertension, and metabolic syndrome in older adulthood (Osher & Stern, 2009; Rillamas-Sun et al., 2014; Villareal et al., 2005; Wee et al., 2005). Most older adults with obesity have multiple chronic conditions, which can result in reduced physical function, decreased quality of life, and higher healthcare costs (Federal Interagency Forum on Aging-Related Statistics, 2012; Rillamas-Sun et al., 2014; Wee et al., 2005). Physical activity, particularly at moderate-to-vigorous intensity levels, has a variety of positive effects on the health of individuals with obesity and chronic conditions (2018 Physical Activity Guidelines Advisory Committee, 2018; Physical Activity Guidelines Committee, 2008). Yet, older adults with obesity have lower rates of meeting physical activity guidelines (Watson et al., 2016). Older adults and people with obesity face many barriers to physical activity, including pain, fatigue, lack of enjoyment, cost, poor weather, and lack of facilities (Brawley, Rejeski, & King, 2003; Ekkekakis, Vazou, Bixby, & Georgiadis, 2016; Lee, Ory, Yoon, & Forjuoh, 2013; Moschny, Platen, Klaassen-Mielke, Trampisch, & Hinrichs, 2011; Zabatiero et al., 2016). Many older adults, particularly those with obesity, may not be able to increase their physical activity, given the aforementioned barriers, signifying that alternative approaches to health promotion are needed (Sparling, Howard, Dunstan, & Owen, 2015).

Sedentary behavior is defined as “any waking behavior characterized by an energy expenditure <1.5 metabolic equivalents while in a sitting or reclining posture” (Sedentary Behaviour Research Network, 2012). Common sedentary behaviors include sitting or lying down while watching television, using a computer, or riding in an automobile, all of which have become pervasive. Older adults with obesity spend 10–11 hr per day sedentary (Davis et al., 2011; Shiroma, Freedson, Trost, & Lee, 2013). High sedentary time is associated with greater risks for Type 2 diabetes, all-cause mortality, cardiovascular disease, waist circumference, metabolic syndrome, higher insulin, high blood pressure, endothelial dysfunction, and poorer physical function among older adults (Bankoski et al., 2011; Biswas et al., 2015; Carson et al., 2014; Copeland et al., 2017; Gao, Nelson, & Tucker, 2007; Healy, Matthews, Dunstan, Winkler, & Owen, 2011; Keadle, Conroy, Buman, Dunstan, & Matthews, 2017; Morishima, Restaino, Walsh, Kanaley, & Padilla, 2017; Wirth et al., 2017). Regular breaks from sitting are associated with lower waist circumference and more favorable systolic blood pressure, cholesterol, and glucose and insulin levels (Carson et al., 2014; Chastin, Egerton, Leask, & Stamatakis, 2015; Duvivier et al., 2018; Hamilton, 2018; Healy et al., 2008; Henson et al., 2016; Wirth et al., 2017; Yates et al., 2020). However, the field lacks data from randomized trials to confirm the findings from epidemiologic and lab studies.

Several one-arm feasibility studies show that reducing sitting time is acceptable to older adults. These studies have demonstrated 30–60 min per day reductions in sitting time (Fitzsimons et al., 2013; Gardiner, Eakin, Healy, & Owen, 2011; Kerr et al., 2016; Lewis et al., 2016; Lyons, Swartz, Lewis, Martinez, & Jennings, 2017; Rosenberg et al., 2015). However, these prior studies were short term (<8 weeks), lacked a control group, and did not measure health outcomes. Based on our pilot work, we developed an intervention for sitting reduction that we termed “I-STAND” (not an acronym), which includes brief health coaching contacts, a wearable device to prompt breaks from sitting, and goals to reduce sitting time by standing and moving more. The primary aim of this study was to determine the effects of I-STAND compared with a control condition in a randomized controlled trial to reduce sitting time in adults over the age of 60 with obesity. A secondary goal was to explore changes in cardiometabolic (fasting glucose, cholesterol, and blood pressure) and functional health (Short Physical Performance Battery) outcomes.

Methods

Study Overview

We conducted a 12-week single blind, randomized two-arm trial to evaluate the efficacy of the I-STAND intervention for reducing sitting time compared with a healthy living control group among older adults with obesity. The participants were enrolled on a rolling basis from February 2016 to February 2017. The study was conducted at Kaiser Permanente Washington. All activities were reviewed and approved by the Kaiser Permanente Washington Institutional Review Board.

Recruitment

Potential participants were identified using electronic health records (EHR) from the membership panels of Kaiser Permanente Washington. Individuals were deemed potentially eligible if they received primary care at a clinic within King County, Washington, were aged 60–89 years, their body mass index (BMI) was ≥30 kg/m2, and their enrollment in the health plan was continuous for 12 months prior to the data extraction date. Individuals were excluded if they resided in long-term care or skilled nursing in the prior 12 months, or had a diagnosis of cancer, heart failure, dementia, or a serious mental health disorder within 12 months prior to the data extraction, according to the diagnostic codes in the EHR.

Between February 2016 and February 2017, study invitation letters were mailed in batches to a random selection of those identified as potentially eligible based on EHR as described above. The letter described the study and invited participants to call a study line if they were interested in learning more about the study. Members were mailed letters up to three times if they did not respond or opted out of further contact. The interested participants were screened by phone for additional eligibility criteria, which were self-reported sitting greater than 6 hr per day, being able to stand, and being able to walk one block with or without an assistive device. These criteria were to ensure a sedentary population who could safely change their sitting behavior in an unsupervised intervention.

Procedures

Those who were screened as eligible and interested provided oral informed consent to participate and were scheduled for an inperson baseline assessment and first intervention session approximately 2–3 weeks after the recruitment phone call. In advance of this meeting, each person was mailed a sleep log, an activPAL (PAL Technologies Ltd., Glasgow, UK) device, and detailed photo-illustrated instructions on how to affix and wear the device for 7 days prior to their visit. If the participants had questions or problems with the device, they were asked to call the study staff for assistance. During the in-person visit, the participants first met with a blinded research specialist and provided written informed consent, had their activPAL data downloaded, completed surveys and biometric assessments, and had a fasting blood draw. After completing all assessments, the participants met with a study health coach, who completed the preliminary processing of the activPAL data to determine the participants’ baseline average daily sedentary time. The participants were then randomized to an intervention group (I-STAND or healthy living) based on 1:1 allocation with randomization stratified by the baseline activPAL measured sedentary time (≥9 hr vs. <9 hr), in permuted blocks of randomly varying size (two or four). Randomization was conducted by the study statistician using a randomized sequence generator, and the sequence was concealed until after completion of the baseline assessment. The health coach then completed the first intervention session with each participant. All assessments, including another previsit 7-day activPAL assessment, were repeated at 12 weeks post randomization, between May 2016 and May 2017. The assessment staff were professionals trained to conduct all measures by the lead study researcher (D.E. Rosenberg) and were blinded to the participants’ randomization assignment. The participants received a total of $100 for completing the baseline and 12-week assessments.

I-STAND Intervention

The intervention was based on our prior pilot work (Greenwood-Hickman, Renz, & Rosenberg, 2016; Rosenberg et al., 2015), and relevant behavioral theories including social–cognitive theory (McAlister, Perry, & Parcel, 2008), the ecological model (McLeroy, Bibeau, Steckler, & Glanz, 1988), and habit formation theory (Gardner, Lally, & Wardle, 2012). Along with written materials, the participants received two in-person health coaching sessions of 30–60 min 1 week apart and four follow-up health coaching phone calls of 15–30 min that tapered over the remaining 10 weeks of the intervention. The participants were taught how to develop strategies to remind them to take breaks from sitting regularly throughout the day. The strategies centered around how to remind oneself to take regular breaks from sitting, including using inner reminders (mindfulness of how the body feels), outer reminders (prompts and cues including a wrist-worn prompting device), and habit reminders (adding bouts of standing to habits one already engages in, such as standing while drinking a morning tea or coffee, standing when talking on the phone). The wrist-worn device, a Jawbone UP band, was preset to provide gentle vibrations every 15 min to cue breaks from sitting throughout the day. The participants were not given the Jawbone smartphone application, nor any other feedback from the device. The participants worked with their health coach to set individual goals around when (days, times) and how they would use the different reminder strategies, including the prompts from the Jawbone UP band. In addition to the baseline and 12-week assessments, the I-STAND participants wore the activPAL two additional times (Week 1 and Week 6) and were provided feedback charts after each time they wore the activPAL (provided in person after the baseline and Week 1 and by mail after the 6- and 12-week time points). The charts depicted their sitting, standing, and stepping time, as well as their sit-to-stand transitions and number of 30-min periods of sitting. The participants set personalized goals each time they met with their health coach, which focused on breaking up sitting regularly and adding in bouts of standing or moving, based on their preferences and abilities. Goals built toward achieving a 60 min per day reduction in sitting over the course of 12 weeks. Finally, different topics were introduced during each session, such as using the home environment to support standing and social norms and support.

Healthy Living Control Condition

The participants received one in-person health coaching session of 30–60 min following the baseline assessment visit and five follow-up contacts by mail. The program was based on the usual care available to members of Kaiser Permanente Washington in the form of a workbook with healthy living education content (e.g., healthy eating, stress management, and preventing falls). Every 2 weeks after the in-person session, healthy living participants were mailed a check-in form to update their health coach on their self-study goals.

Health Coach Training & Fidelity

Two health coaches delivered both arms of the intervention. Both had relevant degrees, but no prior experience with health coaching. They were trained by the team’s licensed clinical psychologist in using motivational interviewing strategies (e.g., reflective listening, open-ended questions, and affirmations) and problem-solving techniques to support behavior change. A health coach guide and structured scripts were used for each session to enhance fidelity. Initial sessions were audio recorded and reviewed by the team’s clinical psychologist to ensure mastery of motivational interviewing techniques and faithful delivery of the intervention content. No formal assessment of fidelity was conducted, but any deviations noted in review were addressed to the coach to correct for future sessions. Contacts were tracked in a Microsoft Access (Seattle, WA) tracking database.

Outcome Measures

The activPAL micro device was used to measure daily sitting time, the primary outcome of this study. Other activPAL variables assessed as secondary outcomes included standing and stepping time, as well as sit-to-stand transitions (i.e., breaks), steps, and bouts of sitting longer than 30 min (i.e., prolonged bouts). We also examined changes in sitting, standing, and stepping time, expressed as a proportion of daily wear time. The activPAL is feasible to use in older populations (Fitzsimons et al., 2013; Lyons et al., 2017), is sensitive to change (Kozey-Keadle et al., 2014), and has excellent validity (Grant, Ryan, Tigbe, & Granat, 2006; Klenk et al., 2016; Kozey-Keadle, Libertine, Lyden, Staudenmayer, & Freedson, 2011; Taraldsen et al., 2011). The device was worn on the front, center thigh and secured with a waterproof dressing. The participants were instructed not to remove the device unless the dressing became compromised or they needed to move the device to the other thigh due to skin irritation. They were given a log to track their sleep time and postage-paid envelopes to return the device. The data were downloaded using proprietary activPAL software, and the “events” file was further processed using programs developed in R (version 3.4.3; R Studio, Boston, MA) for windows, which are not published but are available from the lead author by request. The programs removed sleep time as recorded in logs so that all variables represent waking hours. The data were considered valid if the wear time was greater than 10 hr per day with a minimum of four valid days of data for each assessment period.

Other secondary outcomes, including markers of cardiometabolic and functional health, were also assessed. Physical function was measured with the short physical performance battery to objectively evaluate gait speed, balance, and lower-extremity strength (chair stands; Guralnik et al., 2000; Guralnik, Ferrucci, Simonsick, Salive, & Wallace, 1995; Guralnik et al., 1994). The total scores range from 1 to 12, with scores over 9 indicating high physical function. Cardiometabolic outcomes were assessed by finger-prick blood draw with the Cholestech LDX System machine (Abbott, Mississauga, Ontario, Canada) and cassettes and included fasting glucose and a cholesterol panel (Donato et al., 2015). This system has been established as having acceptable accuracy compared with venous blood samples (Bastianelli, Ledin, & Chen, 2017). Blood pressure was measured using the Omron HEM-907XL digital monitor (Omron Healthcare, Kyoto, Japan). Weight was measured with a calibrated portable digital scale (Tanita HD-351, Tanita, Tokyo, Japan), height with a stadiometer (Seca 213, Seca North America, Chino, CA), and waist circumference with the mean of two measurements taken at the superior border of the iliac crest.

Satisfaction with the I-STAND intervention was assessed in the 12-week survey, including satisfaction with the helpfulness of the intervention components (workbook, in-person sessions, setting goals, action plans, coaching calls, Jawbone, and feedback chart) on a scale from 0 (did not use) to 3 (very helpful). Satisfaction with health coaches, the activPAL, length of the study, and the program’s ability to improve health were rated on a scale from 1 (not satisfied) to 4 (very satisfied). Adherence was measured as the number of health coaching sessions completed by the I-STAND participants.

Potential Covariates

Demographic variables were assessed primarily through the baseline survey (age, race/ethnicity, education, and work status). Sex was obtained from EHR. Health conditions were ascertained by self-report on the baseline survey, by asking whether they had ever experienced any of 20 different chronic conditions.

Statistical Analysis

We used descriptive statistics to summarize the baseline characteristics of the study sample, overall and by randomization group. For all outcomes, linear regression models were used to estimate the difference in mean change from the baseline to 12 weeks between the control and intervention groups. In the primary analyses, the models were adjusted only for the baseline values of the outcome. We also conducted fully adjusted models that additionally adjusted for age, sex, diabetes, and activPAL wear time (for activPAL outcomes only). The analyses of glucose and other blood panel measures were limited to the participants who were fasting at both the baseline and follow-up blood draw. We described the percentage reporting satisfaction with different I-STAND components, as well as adherence metrics. All analyses used a complete case approach, but we conducted sensitivity analyses, which included all randomized participants, to assess the potential impact of study dropout. Sensitivity analyses defined the missing study outcomes as “no change” (baseline value carried forward) for the participants lost to follow-up. All analyses followed an intent-to-treat approach, with study participants analyzed based on randomization group assignment, regardless of intervention participation. Stata (version 15.0; StataCorp LLC, College Station, TX; StataCorp, 2017) statistical software was used for all analyses.

Power Analysis

Based on our prior work, we estimated that the change from the baseline in sitting time adjusted for wear time would have an SD of 8.3%. Assuming an 80% follow-up rate, the sample of 60 (30 in each arm) was estimated to provide 80% power to detect a between-group difference in change in sitting time adjusted for wear time of ~60 min per day. Thus, the study was powered to detect significant differences in the main outcome, but was not powered to detect significant differences in secondary outcomes.

Results

In total, 759 people were sent invitation letters, and 111 called in to the study phone line, interested in participation (see Figure 1). Sixty people were randomized (n = 29 to I-STAND and 31 to the control). There were six participants who dropped out of the control arm. The study participants are described in Table 1.

Figure 1 —

Figure 1 —

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CONSORT diagram.

Table 1.

Study Sample Characteristics (N = 60)

Characteristics Total sample (N = 60) I-STAND (n = 29) Control (n = 31)
Sociodemographic and self-reported comorbidity
 Age (years), M ± SD 68.4 ± 4.9 69.0 ± 4.7 67.8 ± 5.2
 Female, n (%) 41 (68.3) 20 (69.0) 21 (67.7)
 Retired, n (%) 39 (66.1) 18 (62.1) 21 (70.0)
 Race/ethnicity, n (%)
  White 51 (86.4) 28 (96.6) 23 (76.7)
  Black 5 (8.5) 1 (3.5) 4 (13.3)
  Other/multiracial 3 (5.1) 0 (0.0) 3 (10.0)
 Education, college degree or higher, n (%) 46 (78.0) 22 (75.9) 24 (80.0)
 BMI, M ± SD 35.4 ± 4.9 35.7 ± 5.9 35.1 ± 3.7
 Diabetes, n (%) 14 (23.7) 10 (34.5) 4 (13.3)
 Hypertension, n (%) 36 (61.0) 20 (69.0) 16 (53.3)
 Arthritis, n (%) 31 (52.5) 15 (51.7) 16 (53.3)
 Cancer, n (%) 11 (18.6) 3 (10.3) 8 (26.7)
 Sleep disorder, n (%) 21 (35.6) 9 (31.0) 12 (40.0)
 Number of chronic health conditions,a M ± SD 4.4 ± 2.4 4.5 ± 2.9 4.3 ± 1.8
Baseline activPAL activity measures
 Baseline sitting time (hr per day), M ± SD 9.8 ± 1.8 9.7 ± 1.9 9.9 ± 1.8
 Baseline step counts per day, median (25th, 75th percentiles) 5,566 (4,506, 7,078) 5,586 (4,699, 6,795) 5,437 (4,429, 7,088)
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Note. Missing: age (1), retired (1), race/ethnicity (1), education (1), diabetes (1), hypertension (1), arthritis (1), cancer (1), sleep disorder (1), and number of comorbid conditions (1).

a

Number of chronic health conditions participant indicated they had currently or in the past, out of the 20 conditions assessed in the baseline survey.

On average, the participants wore the activPAL device for 6.7 days and 14.9 hr per day at the baseline and 6.4 days and 14.8 hr per day at 12 weeks. One participant in the control condition did not have the minimum of 4 valid wear days at the baseline and was excluded from analyses of activPAL outcomes.

Changes in ActivPAL Measured Outcomes

In models only adjusted for baseline values, the reduction in sitting time was significantly greater for the I-STAND compared with the control participants (difference between groups −58.0 min per day, p = .007; see Table 2).

Table 2.

ActivPAL Measured Outcomesa at Baseline and 12 Weeks

Measure Baseline (M ± SD) Follow-up (M ± SD) Difference in mean change from baseline (I-STAND vs. control; mean differenceb [95% CI]) p value
Sitting time (min per day) −58.0 [−100.3, −15.6] .007
 I-STAND 584 ± 116 528 ± 137
 Control 600 ± 85 600 ± 104
Percentage of the day sitting −5.6 [−9.6, −1.6] .006
 I-STAND 66.1 ± 12.5 60.1 ± 14.0
 Control 66.2 ± 9.0 65.8 ± 9.3
Standing time (min per day) 41.1 [8.5, 73.7] .014
 I-STAND 224 ± 113 266 ± 115
 Control 230 ± 72 230 ± 66
Percentage of the day standing 5.3 [1.7, 8.8] .004
 I-STAND 25.1 ± 11.6 30.7 ± 13.5
 Control 25.2 ± 7.4 25.5 ± 7.8
Stepping time (min per day) 2.2 [−8.3, 12.7] .68
 I-STAND 78 ± 25 81 ± 22
 Control 78 ± 24 79 ± 24
Percentage of the day stepping 0.5 [−0.7, 1.6] .42
 I-STAND 8.8 ± 2.7 9.3 ± 2.4
 Control 8.6 ± 2.5 8.7 ± 2.5
Breaks −3.4 [−9.5, 2.8] .28
 I-STAND 51 ± 14 51 ± 13
 Control 56 ± 18 59 ± 21
Prolonged bouts −1.4 [−2.3, −0.5] .003
 I-STAND 5.9 ± 1.9 4.4 ± 2.0
 Control 5.5 ± 1.4 5.6 ± 1.6
Step count 351 [−646, 1,348] .49
 I-STAND 6,016 ± 2,281 6,302 ± 2,366
 Control 5,887 ± 2,050 5,877 ± 2,005
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Note. CI = confidence interval.

a

Limited to 53 participants (n = 29 I-STAND; n = 24 control) with valid activPAL data at both baseline and follow-up.

b

Models are adjusted for baseline measure of the outcome.

The I-STAND participants also had greater increases in standing time (41.1 min per day; p = .014) and decreases in prolonged sitting bouts (−1.4 bouts, p = .003), favoring the I-STAND condition. There were no significant differences between groups for changes in stepping time, breaks from sitting, or step counts. Confirming these results, changes in sitting time when expressed as a percentage of wear time also favored the I-STAND group (difference between groups 5.6%; p = .006), as did improvements in the percentage of the day spent standing (5.3%; p = .004). The pattern of results was similar in the models adjusted for wear time, age, sex, and diabetes and in the sensitivity analyses conducted on all participants with valid baseline activPAL data (n = 59), so we only presented results for the more parsimonious models.

Changes in Cardiometabolic and Functional Outcomes

A total of 15 I-STAND and 18 healthy living participants had fasting blood work available for the glucose and cholesterol analyses at both the baseline and 12 weeks. There were no significant differences between groups in changes in these biomarker outcomes (see Table 3).

Table 3.

Secondary Biomarker Outcomes Measured at Baseline and 12 Weeks Adjusting for Baseline Values (n = 34)a

Measure Baseline (M ± SD) Follow-up (M ± SD) Difference in mean Change from baseline (I-STAND vs. control; mean differenceb [95% CI]) p value
Glucose (mg/dL) −0.30 [−8.9, 8.3] .95
 I-STAND 105.6 ± 15.6 107.7 ± 26.5
 Control 102.5 ± 14.6 105.0 ± 10.3
Triglycerides (mg/dL) 10.5 [−13.8, 34.8] .40
 I-STAND 117.9 ± 32.4 129.1 ± 40.6
 Control 129.6 ± 58.7 126.5 ± 53.5
HDL cholesterol (mg/dL) −0.68 [−6.3, 5.0] .81
 I-STAND 55.4 ± 12.3 55.9 ± 15.4
 Control 58.4 ± 19.6 59.4 ± 19.2
LDL cholesterol (mg/dL) 5.4 [−10.5, 21.4] .51
 I-STAND 110.7 ± 28.8 115.9 ± 40.8
 Control 113.2 ± 38.8 112.7 ± 37.5
Total cholesterol (mg/dL) 8.4 [−9.7, 26.4] .36
 I-STAND 189.9 ± 35.2 197.5 ± 42.5
 Control 199.4 ± 43.8 197.7 ± 46.3
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Note. CI = confidence interval; HDL = high-density lipoprotein; LDL = low-density lipoprotein.

a

All biomarker measures are limited to 34 participants with fasting blood work at both baseline and follow-up. One control participant was missing LDL-cholesterol at baseline and is excluded for the LDL outcome only.

b

Models are adjusted for baseline measure of the outcome.

There were small but insignificant differences in improvements for other health outcomes, including blood pressure (systolic −3.93, p = .24; diastolic −2.97, p =.14), weight (−1.8 pounds, p = .16), and BMI (−0.31 kg/m2, p = .19) favoring I-STAND (see Table 4). The results were similar in the models adjusted for age, sex, and diabetes.

Table 4.

Secondary Cardiometabolic and Functional Health Outcomes at Baseline and 12 Weeks (N = 54a)

Measure Baseline (M ± SD) Follow-upb (M ± SD) Difference in mean change from baseline (I-STAND vs. control; mean differencec [95% CI]) p value
Systolic blood pressure (mmHg) −3.93 [−10.5, 2.7] .24
 I-STAND 130.7 ± 17.4 127.2 ± 15.8
 Control 134.8 ± 17.8 133.3 ± 14.0
Diastolic blood pressure (mmHg) −2.97 [−6.9, 1.0] .14
 I-STAND 74.6 ± 10.1 72.7 ± 8.8
 Control 77.4 ± 11.6 76.9 ± 7.9
Weight (lb) −1.80 [−4.3, 0.7] .16
 I-STAND 220.0 ± 39.9 218.6 ± 39.8
 Control 214.1 ± 39.3 214.7 ± 38.7
Waist circumference (in.) −0.52 [−1.3, 0.3] .20
 I-STAND 45.3 ± 6.1 45.0 ± 6.2
 Control 44.7 ± 4.2 44.9 ± 4.5
BMI (kg/m2) −0.31 [−0.8, 0.1] .19
 I-STAND 35.7 ± 5.9 35.5 ± 5.9
 Control 35.0 ± 3.8 35.0 ± 3.9
Gait speed (s) 0.03 [−0.1, 0.2] .70
 I-STAND 3.13 ± 0.51 3.11 ± 0.52
 Control 3.24 ± 0.76 3.18 ± 0.84
Chair stands (s) 0.40 [−0.6, 1.4] .82
 I-STAND 10.7 ± 3.3 10.2 ± 3.0
 Control 11.6 ± 7.4 10.2 ± 2.9
SPPB total score −0.28 [−0.8, 0.2] .30
 I-STAND 11.2 ± 1.3 11.1 ± 1.8
 Control 11.2 ± 1.7 11.4 ± 1.8
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Note. SPPB = Short Physical Performance Battery. Missing values: systolic blood pressure (1), diastolic blood pressure (1), gait speed (1), chair stands (2), and SPPB (3).

a

Limited to 54 participants who completed both the baseline and 12-week assessment.

b

Follow-up results adjusted for baseline values.

c

Models are adjusted for baseline measure of the outcome.

I-STAND Intervention and Study Satisfaction and Adherence

The workbook, in-person sessions, goal setting, action plans, health coaching phone calls, and feedback charts were rated as somewhat or very helpful by all I-STAND participants. Two people reported not using the Jawbone, and four people reported that it was not helpful, with the remainder (23 people; 79%) reporting that it was somewhat or very helpful. All I-STAND participants reported being very satisfied with their health coach. Satisfaction with the activPAL device was high overall, with 89% of the participants reporting they were satisfied or very satisfied with it. For the length of the study and the program’s ability to improve health, 85% and 92% were satisfied or very satisfied, respectively. Overall, 97% of the I-STAND participants completed all six health coaching sessions.

Adverse Events

There were no serious adverse events. Mild skin irritation was the only adverse event (two related to activPAL and three from the Jawbone UP band).

Discussion

Overall, we found that a sitting reduction intervention reduced sitting time, improved standing time, and resulted in fewer prolonged sitting bouts compared with a control condition in older adults with obesity. Our sample had high levels of sitting time at the baseline, on average 9.8 hr per day, and the steps per day were well below the 7,000 steps per day minimum suggested for older adults or people with chronic conditions (Tudor-Locke et al., 2011). Our results are stronger than some prior one-arm studies (Fitzsimons et al., 2013; Gardiner et al., 2011; Rosenberg et al., 2015) and a recent randomized controlled trial in cardiac rehabilitation patients (Prince et al., 2018), finding around ~30-min reductions in sitting time (Kerr et al., 2016; Lewis et al., 2016). The intervention was safe, and the participants had high satisfaction ratings. Older adults with obesity may be more amenable to and capable of increasing their standing time as compared with changing their physical activity. In prior research, standing has been associated with improvements in insulin and glucose and small increases in energy expenditure over sitting (Edwardson et al., 2017; Gibbs, Kowalsky, Perdomo, Grier, & Jakicic, 2017; Henson et al., 2016; Swartz, Squires, & Strath, 2011).

In the I-STAND arm, the study goal was to reduce sitting by 60 min per day through a combination of standing more and taking frequent, brief breaks from sitting. This streamlined goal was feasible, as our adjusted difference in change in sitting time between groups was approximately 58 min per day. While the intervention was effective in reducing sitting time, it did not appreciably alter physical activity. Physical activity interventions do not appreciably alter sedentary time (Martin et al., 2015; Prince, Saunders, Gresty, & Reid, 2014), so perhaps it makes sense, according to behavioral specificity principles, that sedentary behavior reduction interventions do not appreciably alter physical activity. The steps did increase by a small amount, by 286 per day on average in the I-STAND group compared with no change in the control condition.

Breaks from sitting were not impacted by the intervention. However, this metric may not be helpful because the less sitting people engage in, the fewer opportunities they have to break from sitting. A better metric may be prolonged sitting bouts (sitting for 30 min or more), which were reduced by over one bout per day with the I-STAND intervention, indicating that the participants were successful in changing their sitting patterns.

There were no significant changes in secondary cardiometabolic and functional health outcomes. Although our study was not powered to observe differences in health outcomes, there were a few potentially interesting patterns, specifically, trends in the positive direction for weight, BMI, waist circumference, and blood pressure. Reductions in blood pressure were similar to trials that promote physical activity (Diaz & Shimbo, 2013). A recent meta-analysis suggested that aerobic exercise trials reduce diastolic blood pressure by −3.68 mmHg and systolic blood pressure by −5.39 mmHg (Huang et al., 2013). We found nearly 3-mmHg reductions in diastolic blood pressure associated with the I-STAND intervention, and data suggests that reductions as small as 2 mmHg may lead to a large decrease in the prevalence of hypertension (Diaz & Shimbo, 2013). For SBP, the difference was nearly 4 mmHg, which is similar to the results of exercise trials.

Study limitations include a small sample size and short time frame. Our study was not powered to detect changes in our secondary cardiometabolic and functional health outcomes. To observe health improvements, we may have needed a greater reduction in sitting time, a larger sample size, or a longer time period for changes in behavior to impact metabolic outcomes. There was differential dropout by group (the only dropouts occurred in the control group), indicating that the control group content may not have been well liked and or there was insufficient attention paid to the participants. We recommend the use of attention control conditions in future studies. There may have been ceiling effects for some measures, such as the short physical performance battery, due to the study inclusion criteria. Using functional measures that have better sensitivity to change or including those with more limitations could be important for future work. Additionally, we cannot rule out that those in the I-STAND arm could have been motivated to decrease their sitting time more when wearing the activPAL device, and this could bias the results. Better tools that provide real-time feedback on sitting time are needed to avoid this problem in future studies. Our generalizability is limited because of our low recruitment response rate, and our sample was primarily White, female, and educated. We did not assess diet, which plays an important role in obesity and may be related to cardiometabolic markers. Future studies could assess diet or control for it in an intervention. The strengths of our study include that it is one of the only randomized controlled trials of sitting reduction in older adults and the first, to our knowledge, in older adults with obesity, a high-risk population. We were also able to use objective outcome measures for sitting time and indicators of cardiometabolic and functional health risk. We were able to reach a population with a high burden of chronic conditions, high BMI, and low physical activity.

Conclusions

In total, older adults with obesity successfully reduced their sitting time by increasing their standing time. Messages to sit less for populations with obesity and other populations that struggle with physical activity could be encouraged more broadly, such as through medical settings. Future studies are needed to examine whether sitting behaviors can be reduced and sustained over longer time periods and whether there are health impacts from standing more, and to determine which intervention components are most beneficial.

Acknowledgments

This work was funded by the National Institutes of Health and the National Institute on Aging (K23HL119352, R21AG043853). These funding bodies played no direct role in the design of the study; collection, analysis, or interpretation of data; or in writing this manuscript. The authors declare that there is no conflict of interest. All study protocols and procedures were reviewed and approved by Kaiser Permanente Washington’s institutional review board. Signed informed consent was obtained from all subjects prior to participation in the study. The datasets generated and/or analyzed during the current study are not publicly available to protect the privacy of our study participants, but are available from the corresponding author on reasonable request.

Contributor Information

Dori E. Rosenberg, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Melissa L. Anderson, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Anne Renz, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.

Theresa E. Matson, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Amy K. Lee, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Mikael Anne Greenwood-Hickman, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.

David E. Arterburn, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Paul A. Gardiner, Centre for Health Services Research, The University of Queensland, Brisbane, Queensland, Australia. Kerr is with The Grant Doctor, San Diego, CA, USA

Jacqueline Kerr, The Grant Doctor, San Diego, CA, USA.

Jennifer B. McClure, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

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