Determinants of physical activity in America: a first characterization of physical activity profile using the National Health and Nutrition Examination Survey (NHANES)

Mind the gap: Habit and self-determined motivation predict health behaviours in middle-aged and older adults

OBJECTIVES

Physical activity and fruit and vegetable consumption are two key health behaviours associated with the health and well-being of middle-aged and older adults. The present research investigated how habit and self-determined motivation interact with intention to prospectively predict physical activity and fruit and vegetable consumption in middle-aged and older adults.

DESIGN

A prospective correlational design (two data collection points) was used.

METHODS

A convenience sample of 195 adults completed online questionnaires measuring intention, habit, and self-determined motivation. One week later, 177 participants (67.2% female), aged 52-87 years (M = 61.50, SD = 5.90), completed self-report measures of physical activity and fruit and vegetable consumption over the previous week.

RESULTS

Separate hierarchical multiple regression analyses were conducted. For physical activity, the model explained 46% of the variance in behaviour, F(8, 168) = 17.88, p < .001 and a large effect size (ƒ2  = .85). Two-way interactions contributed an additional 3.70% of unique variance in physical activity, F(3, 165) = 4.07, p = .008, ƒ2  = .04. For fruit and vegetable consumption, the model explained 19.20% of the variance in behaviour, F(5, 171) = 8.13, p < .001 and a medium effect size (ƒ2  = .24). Two-way interactions did not significantly improve the model, F(3, 168) = 1.68, p = .174.

CONCLUSIONS

Habit and self-determined motivation were both important in narrowing the intention-behaviour gap for two key health behaviours, and combining these processes may better inform strategies to support people's intentions to improve these health behaviours.

Demographic, Socioeconomic, and Health-Related Predictors of Objectively Measured Sedentary Time and Physical Activity During Pregnancy

BACKGROUND

Sedentary behavior (SED) and moderate-to-vigorous intensity physical activity (MVPA) have important implications for health; however, little is known about predictors of these behaviors during pregnancy.

METHODS

This cohort study measured SED (activPAL) and MVPA (GT3X) in each trimester of pregnancy. Univariate associations of demographic, socioeconomic, and pregnancy health-related factors with SED or MVPA were calculated. Associations with P < .10 were included in stepwise linear regression models to determine independent predictors in each trimester.

RESULTS

Pregnant women (n = 127) were age 31.0 (4.9) years and 78% white. In regression models across trimesters, fewer children ≤ age 5 in the household (P < .04) and primarily sitting job activity (P < .008) were related to higher SED and use of assisted reproductive technology (P < .05) was associated with higher MVPA. In at least one trimester, younger age was related to higher SED (P = .014); no history of pregnancy loss (P < .04), being married (P = .003), employed (P < .004, full time or student), white race (P = .006), and higher education (P = .010) were associated with higher MVPA.

CONCLUSIONS

Predictors of SED in pregnancy were more consistent, and differed from predictors of MVPA. These findings may help identify women at risk of high SED or low MVPA, though future research in larger samples is needed.

Smoking Is Associated with Pain in All Body Regions, with Greatest Influence on Spinal Pain

OBJECTIVE

Examine the interrelationship between smoking and pain in the US population.

DESIGN

A cross-sectional population-based study.

SETTING

Nationwide survey.

METHODS

Comprehensive pain reports categorically defined as head, spine, trunk, and limb pain; smoking history; demographics; medical history from a total of 2,307 subjects from the 2003-2004 National Health and Nutrition Examination Survey obtained from the Centers for Disease Control were analyzed. Unpaired t tests were used to analyze independent continuous variables, and chi-square tests were used to analyze categorical variables between smoker and nonsmoker groups. Weighted multivariate logistic regression analyses determined the association of current smoking with the presence of pain in various body regions.

RESULTS

Smoking is most strongly associated with spine pain (odds ratio [OR] = 2.89, 95% confidence interval [CI] = 2.21-3.77), followed by headache (OR = 2.47, 95% CI = 1.73-3.53), trunk pain (OR = 2.17, 95% CI = 1.45-2.74), and limb pain (OR = 1.99, 95% CI = 1.45-2.73).

CONCLUSIONS

Current smoking is associated with pain in every region of the body. This association is strongest for spine and head pain. Given that pain is a strong motivator and that current smoking was associated with pain in all body regions, we recommend that these results be used to further raise public awareness about the potential harms of smoking.

Differences in objectively measured daily physical activity patterns related to depressive symptoms in community dwelling women - mPED trial

Physical activity (PA) is an effective depression treatment. However, knowledge on how variation in day-to-day PA relates to depression in women is lacking. The purposes of this study were to 1) compare overall objectively measured baseline daily steps and duration of moderate to vigorous PA (MVPA) and 2) examine differences in steps and MVPA on days of the week between women aged 25–65 years, who were physically inactive, with high and low depressive symptoms, enrolled in a run-in period of the mobile phone based physical activity education (mPED) trial. The Center for Epidemiological Studies Depression Scale was used to categorize low/high depressive symptom groups. We used linear mixed-effects models to examine the associations between steps and MVPA and depression-status overall and by day of the week, adjusting for selected demographic variables and their interactions with day of the week. 274 women were included in the final analysis, of which 58 had high depressive symptoms. Overall physical activity levels did not differ. However, day of the week modified the associations of depression with MVPA (p = 0.015) and daily steps (p = 0.08). Women with high depression were characterized by reduced activity at the end of the week (Posthoc: Friday: 791 fewer steps, 95% CI: 73–1509, p = 0.03; 8.8 lower MVPA, 95% CI: 2.16–15.5, p = 0.0098) compared to women with low depression, who showed increased activity. Day of the week might be an important target for personalization of physical activity interventions. Future work should evaluate potential causes of daily activity alterations in depression in women.

A trajectory analysis of daily step counts during a physician-delivered intervention

OBJECTIVES

Higher steps are associated with lower mortality and cardiovascular event rates. We previously demonstrated that tailored physician-delivered step count prescriptions successfully increased steps/day in adults with type 2 diabetes mellitus (T2DM) and/or hypertension. In the present analysis, we examined patterns of step count change and the factors that influence different responses.

DESIGN

Longitudinal observational study METHODS: Active arm participants (n=118) recorded steps/day. They received a step count prescription from their physician every 3-4 months. We computed mean steps/day and changes from baseline for sequential 30-day periods. Group-based trajectory modeling was applied.

RESULTS

Four distinct trajectories of mean steps/day emerged, distinguishable by differences in baseline steps/day: sedentary (19%), low active (40%), somewhat active (30%) and active (11%). All four demonstrated similar upward slopes. Three patterns emerged for the change in steps from baseline: gradual decrease (30%), gradual increase with late decline (56%), and rapid increase with midpoint decline (14%); thus 70% had an increase from baseline. T2DM (odd ratios [OR]: 3.7, 95% CI 1.7, 7.7) and age (OR per 10-year increment: 2, 95% CI 1.3, 2.8) were both associated with starting at a lower baseline but participants from these groups were no less likely than others to increase steps/day.

CONCLUSIONS

T2DM and older age were associated with lower baseline values but were not indicators of likelihood of step count increases. A physician-delivered step count prescription and monitoring strategy has strong potential to be effective in increasing steps irrespective of baseline counts and other clinical and demographic characteristics.

Physical Activity Levels in Peripheral Artery Disease Patients

Background

Increases in daily physical activity levels is recommended for patients with peripheral artery disease (PAD). However, despite this recommendation, little is known about the physical activity patterns of PAD patients.

Objective

To describe the physical activity patterns of patients with symptomatic peripheral artery (PAD) disease.

Methods

This cross-sectional study included 174 PAD patients with intermittent claudication symptoms. Patients were submitted to clinical, hemodynamic and functional evaluations. Physical activity was objectively measured by an accelerometer, and the time spent in sedentary, low-light, high-light and moderate-vigorous physical activities (MVPA) were obtained. Descriptive analysis was performed to summarize patient data and binary logistic regression was used to test the crude and adjusted associations between adherence to physical activity recommendation and sociodemographic and clinical factors. For all the statistical analyses, significance was accepted at p < 0.05.

Results

Patients spent in average of 640 ± 121 min/day, 269 ± 94 min/day, 36 ± 27 min/day and 15 ± 16 min/day in sedentary, low-light, high-light and MVPA, respectively. The prevalence of patients who achieved physical activity recommendations was 3.4%. After adjustment for confounders, a significant inverse association was observed between adherence to physical activity recommendation and age (OR = 0.925; p = 0.004), while time of disease, ankle brachial index and total walking distance were not associated with this adherence criteria (p > 0.05).

Conclusion

The patterns of physical activity of PAD patients are characterized by a large amount of time spent in sedentary behaviors and a low engagement in MVPA. Younger patients, regardless of the clinical and functional factors, were more likely to meet the current physical activity recommendations.

Short- and Long-term Effects of a Mobile Phone App in Conjunction With Brief In-Person Counseling on Physical Activity Among Physically Inactive Women: The mPED Randomized Clinical Trial

IMPORTANCE

Mobile phone applications (apps) and activity trackers allow researchers to remotely deliver an intervention and monitor physical activity but have not been rigorously evaluated for longer periods.

OBJECTIVE

To determine whether a mobile phone-based physical activity education app, in conjunction with brief in-person counseling, increases and then maintains levels of physical activity.

DESIGN, SETTING, AND PARTICIPANTS

In this parallel randomized clinical trial, community-dwelling physically inactive women recruited between May 2011 and April 2014 were randomized in equal proportions into the control (n = 69), regular (n = 71), and plus (n = 70) groups. Data were analyzed using intention to treat from September 16, 2016, through June 30, 2018.

INTERVENTIONS

The regular and plus groups were instructed to use the app on their mobile phone and an accelerometer every day for 3 months and attend brief in-person counseling. During the 6-month maintenance period, the plus group continued to use the app and accelerometer, while the regular group stopped using the app but continued using the accelerometer. The control group used the accelerometer throughout.

MAIN OUTCOMES AND MEASURES

The primary and secondary outcomes were daily accelerometer-measured total steps and time spent in moderate to vigorous physical activity (MVPA).

RESULTS

The 210 participants had a mean (SD) age of 52.4 (11.0) years. At baseline, the mean (SD) daily total steps by accelerometer in the control, regular, and plus groups were 5384 (2920), 5063 (2526), and 5837 (3235), respectively. During the 3-month intervention period, daily steps and MVPA increased in the combined regular and plus groups compared with the control group (between-group differences, 2060 steps per day; 95% CI, 1296-2825 steps per day; P < .001 and 18.2 min/d MVPA; 95% CI, 10.9-25.4 min/d MVPA; P < .001). During the subsequent 6-month maintenance period, mean activity level remained higher in the combined plus and regular groups than among controls (between-group difference, 1360 steps per day; 95% CI, 694-2026 steps per day; P <. 001), but trends in total daily steps and MVPA were similar in the plus and regular groups.

CONCLUSIONS AND RELEVANCE

In this trial, the intervention groups substantially increased their physical activity. However, use of both the app and accelerometer for an additional 6 months after the initial 3-month intervention did not help to maintain increases in physical activity compared with continued use of the accelerometer alone.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01280812.

Digital biomarkers of spine and musculoskeletal disease from accelerometers: Defining phenotypes of free-living physical activity in knee osteoarthritis and lumbar spinal stenosis

BACKGROUND CONTEXT

Lumbar spinal stenosis (LSS) and knee osteoarthritis (OA) are 2 of the leading causes of disability worldwide. In order to provide disease-specific prescriptions for physical activity, there is a clear need to better understand physical activity in daily life (performance) in these populations.

PURPOSE

To discover performance phenotypes for LSS and OA by applying novel analytical methods to accelerometry data. Specific objectives include the following: (1) to identify characteristic features (phenotypes) of free-living physical activity unique to individuals with LSS and OA, and (2) to determine which features can best differentiate between these conditions.

STUDY DESIGN AND SETTING

Leveraging data from 3 existing cross-sectional cohorts, accelerometry signal feature characterization and selection were performed in a computational laboratory.

PATIENT SAMPLE

Data from a total of 4,028 individuals were analyzed from the following 3 datasets: LSS Accelerometry Database (n=75); OA Initiative (n=1950); and the 2003 to 2004 National Health and Nutrition Examination Survey (pain-free controls, n=2003).

METHODS

In order to characterize the accelerometry signals, data were examined using (1) standard intervals for counts/minute from Freedson et al. and (2) the physical performance intervals for mobility-limited pain populations. From this, 42 novel accelerometry features were defined and evaluated for significance in discriminating between the groups (LSS, OA, and controls) in order to then determine which sparse set of features best differentiates between the groups. These sparse sets of features defined the performance phenotypes.

OUTCOME MEASURES

Accelerometry features and their ability to differentiate between individuals with LSS, OA, and controls.

RESULTS

Given age and gender, classification rates were at least 80% accurate (pairwise) between diseased and pain-free populations (LSS vs. controls and OA vs. controls). The most important features to distinguish between disease groups corresponded to measures in the light and sedentary activity intervals. The more subtle classification between diseased populations (LSS vs. OA) was 72% accurate, with light and moderate activity providing the prominent distinguishing features.

CONCLUSIONS

We describe the discovery of performance phenotypes of LSS and OA from accelerometry data, revealed through a novel set of features that characterize daily patterns of movement in people with LSS and OA. These performance phenotypes provide a new method for analyzing free-living physical activity (performance) in LSS and OA, and provide the groundwork for more personalized approaches to measuring and improving function.

Group-Based Trajectory Analysis of Physical Activity Change in a US Weight Loss Intervention

BACKGROUND

The obesity epidemic is a global concern. Standard behavioral treatment including increased physical activity, reduced energy intake, and behavioral change counseling is an effective lifestyle intervention for weight loss.

PURPOSE

To identify distinct step count patterns among weight loss intervention participants, examine weight loss differences by trajectory group, and examine baseline factors associated with trajectory group membership.

METHODS

Both groups received group-based standard behavioral treatment while the experimental group received up to 30 additional, one-on-one self-efficacy enhancement sessions. Data were analyzed using group-based trajectory modeling, analysis of variance, chi-square tests, and multinomial logistic regression.

RESULTS

Participants (N = 120) were mostly female (81.8%) and white (73.6%) with a mean (SD) body mass index of 33.2 (3.8) kg/m2. Four step count trajectory groups were identified: active (>10,000 steps/day; 11.7%), somewhat active (7500-10,000 steps/day; 28.3%), low active (5000-7500 steps/day; 27.5%), and sedentary (<5000 steps/day; 32.5%). Percent weight loss at 12 months increased incrementally by trajectory group (5.1% [5.7%], 7.8% [6.9%], 8.0% [7.4%], and 13.63% [7.0%], respectively; P = .001). At baseline, lower body mass index and higher perceived health predicted membership in the better performing trajectory groups.

CONCLUSIONS

Within a larger group of adults in a weight loss intervention, 4 distinct trajectory groups were identified and group membership was associated with differential weight loss.

Optimizing treatment protocols for spinal manipulative therapy: study protocol for a randomized trial

BACKGROUND

Low back pain is a common and costly condition. Spinal manipulative therapy (SMT) is a treatment supported in some guidelines, although most clinical trials examining SMT report small effect sizes. Enhancing the effects of SMT requires an understanding of underlying mechanisms and a systematic approach to leverage understanding of mechanisms to create more effective treatment protocols that are scalable in clinical practice. Prior work has identified effects on spinal stiffness and lumbar multifidus activation as possible mechanisms. This project represents a refinement phase study within the context of a multi-phase optimization strategy (MOST) framework. Our goal is to identify an optimized SMT treatment protocol by examining the impact of using co-intervention exercise strategies that are proposed to accentuate SMT mechanisms. The optimized protocol can then be evaluated in confirmation phase clinical trials and implementation studies.

METHODS

A phased, factorial randomized trial design will be used to evaluate the effects of three intervention components provided in eight combinations on mechanistic (spinal stiffness and multifidus muscle activation) and patient-reported outcomes (pain and disability). All participants will receive two sessions then will be randomly assigned to receive six additional sessions (or no additional treatment) over the next three weeks with factorial combinations of additional SMT and exercise co-interventions (spine mobilizing and multifidus activating). Outcome assessments occur at baseline, and one week, four weeks, and three months after enrollment. Pre-specified analyses will evaluate main effects for treatment components as well as interaction effects.

DISCUSSION

Building on preliminary findings identifying possible mechanisms of effects for SMT, this trial represents the next phase in a multiphase strategy towards the ultimate goal of developing an optimized protocol for providing SMT to patients with LBP. If successful, the results of this trial can be tested in future clinical trials in an effort to produce larger treatment benefits and improve patient-centered outcomes for individuals with LBP.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02868034 . Registered on 16 August 2016.

Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations

Background

Accurate measurement of physical performance in individuals with musculoskeletal pain is essential. Accelerometry is a powerful tool for this purpose, yet the current methods designed to evaluate energy expenditure are not optimized for this population. The goal of this study is to empirically derive a method of accelerometry analysis specifically for musculoskeletal pain populations.

Methods

We extracted data from 6,796 participants in the 2003–4 National Health and Nutrition Examination Survey (NHANES) including: 7-day accelerometry, health and pain questionnaires, and anthropomorphics. Custom macros were used for data processing, complex survey regression analyses, model selection, and statistical adjustment. After controlling for a multitude of variables that influence physical activity, we investigated whether distinct accelerometry profiles accompany pain in different locations of the body; and we identified the intensity intervals that best characterized these profiles.

Results

Unique accelerometry profiles were observed for pain in different body regions, logically clustering together based on proximity. Based on this, the following novel intervals (counts/minute) were identified and defined: Performance Sedentary (PSE) = 1–100, Performance Light 1 (PL1) = 101–350, Performance Light 2 (PL2) = 351–800, Performance Light 3 (PL3) = 801–2500, and Performance Moderate/Vigorous (PMV) = 2501–30000. The refinement of accelerometry signals into these new intervals, including 3 distinct ranges that fit inside the established light activity range, best captures alterations in real-life physical performance as a result of regional pain.

Discussion and conclusions

These new accelerometry intervals provide a model for objective measurement of real-life physical performance in people with pain and musculoskeletal disorders, with many potential uses. They may be used to better evaluate the relationship between pain and daily physical function, monitor musculoskeletal disease progression, gauge disease severity, inform exercise prescription, and quantify the functional impact of treatments. Based on these findings, we recommend that future studies of pain and musculoskeletal disorders analyze accelerometry output based on these new “physical performance” intervals.

Effects of a multicomponent physical activity behavior change intervention on breast cancer survivor health status outcomes in a randomized controlled trial

Little is known about the effects of physical activity behavior change interventions on health outcomes such as lower extremity dysfunction and SF-36 physical health (predictor of mortality) in breast cancer survivors. Furthermore, effect moderators are rarely reported. Therefore, we report the effects of the 3-month BEAT Cancer physical activity behavior change intervention on global health status and health indicators along with moderators of intervention outcomes. Postprimary treatment breast cancer survivors (n = 222) were randomized to BEAT Cancer or usual care (UC). SF-36, muscle strength, body mass index, lower extremity dysfunction (WOMAC), and life satisfaction were measured at 3 months (M3) and 6 months (M6). At M3, adjusted linear mixed-model analyses demonstrated statistically significant effects of BEAT Cancer versus UC on SF-36 physical health [mean between-group difference (M) = 2.1; 95 % confidence interval (CI) 0.3-3.9; p = 0.023], SF-36 mental health (M = 5.2; CI 2.8-7.6; p < 0.001), and all SF-36 subscores. Intervention benefits occurred for lower extremity physical dysfunction (M = -2.7; CI -5.0 to -0.5; p = 0.018), WOMAC total (M = -3.7; CI -6.7 to -0.6; p = 0.018), and life satisfaction (M = 2.4; CI 0.9-3.9; p = 0.001). Statistically significant effects persisted at M6 for mental health and vitality. Baseline value, income, marital status, cancer treatment, cancer stage, and months since diagnosis moderated one or more outcomes. BEAT Cancer improves SF-36, WOMAC, and life satisfaction outcomes with improvements in vitality and mental well-being continuing 3 months postintervention. Several moderators with potential to guide targeting individuals for optimal intervention benefit warrant further study.

Correlates of US adult physical activity and sedentary behavior patterns

OBJECTIVES

Physical activity and sedentary behavior patterns may be differentially associated with socio-demographic and health measures. We explored correlates of day-to-day patterns over a week in accelerometer measured physical activity and sedentary behavior to inform intervention development.

DESIGN

Cross-sectional study.

METHODS

National Health and Nutrition Examination Survey (NHANES) adult participants (≥20 years) in 2003-2006 wore an accelerometer for 1 week. Accelerometer data from 7236 participants were used to derive latent classes describing day-to-day patterns over a week of physical activity and sedentary behavior. Correlates of each pattern were identified using multinomial logistic regression from 21 potential variables grouped into four domains: socio-demographic, acculturation, cardiovascular, and health history.

RESULTS

Older age, female sex, higher body mass index, and history of chronic disease were consistently associated with lower odds of being in a more active compared to the least active class. In contrast, being employed, speaking Spanish at home, and having better self-rated health were associated with higher odds of being in a more active compared to the least active class.

CONCLUSIONS

Correlates of physical activity and sedentary behavior patterns were identified from all domains (socio-demographic, acculturation, cardiovascular, and health history). Most correlates that were positively associated with physical activity were negatively associated with sedentary behavior. Better understanding of the correlates of physical activity and sedentary behavior patterns can inform interventions to promote physical activity and reduce sedentary behavior.

Deviation between self-reported and measured occupational physical activity levels in office employees: effects of age and body composition

OBJECTIVES

Whether occupational physical activity (PA) will be assessed via questionnaires or accelerometry depends on available resources. Although self-reported data collection seems feasible and inexpensive, obtained information could be biased by demographic determinants. Thus, we aimed at comparing self-reported and objectively measured occupational sitting, standing, and walking times adjusted for socio-demographic variables.

METHODS

Thirty-eight office employees (eight males, 30 females, age 40.8 ± 11.4 years, BMI 23.9 ± 4.2 kg/m(2)) supplied with height-adjustable working desks were asked to report sitting, standing, and walking times using the Occupational Sitting and Physical Activity Questionnaire during one working week. The ActiGraph wGT3X-BT was used to objectively measure occupational PA during the same week. Subjectively and objectively measured data were compared computing the intra-class correlation coefficients, paired t tests and Bland-Altman plots. Furthermore, repeated-measurement ANOVAs for measurement (subjective vs. objective) and socio-demographic variables were calculated.

RESULTS

Self-reported data yielded a significant underestimation of standing time (13.3 vs. 17.9%) and an overestimation of walking time (12.7 vs. 5.0%). Significant interaction effects of age and measurement of standing time (F = 6.0, p = .02, ηp(2) = .14) and BMI group and measurement of walking time were found (F = 3.7, p = .04, ηp(2) = .17). Older employees (>39 years) underestimated their standing time, while underweight workers (BMI < 20 kg/m(2)) overestimated their walking time.

CONCLUSIONS

Self-reported PA data differ from objective data. Demographic variables (age, BMI) affect the amount of self-reported misjudging of PA. In order to improve the validity of self-reported data, a correction formula for the economic assessment of PA by subjective measures is needed, considering age and BMI.

Nutrition Promotion to Prevent Obesity in Young Adults

Young adulthood is a vulnerable period for weight gain and the health consequences of becoming obese during this life-stage of serious concern. Some unhealthy dietary habits are typical of young adults in many developed nations encountering the obesity epidemic. These include high sugar-sweetened beverage consumption, lower vegetable intake and greater consumption of foods prepared outside the home including fast foods. Each of these dietary behaviours may place young adults at increased risk for overweight and obesity. Evidence suggests many young adults with unhealthy nutrition behaviours are not considering nor preparing to make changes. To improve their nutrition and health as they progress through the lifecycle requires approaches specifically targeted to this age group. Strategies and programs should include both individual level and population approaches. The evidence base for prevention of weight gain and halting overweight and obesity in young adulthood is currently small with few studies of high quality. Studies modifying food environments in colleges and universities are also of limited quality, but sufficiently promising to conduct further research employing better, more sophisticated, study designs and additionally to include health outcome measures. More research into programs tailored to the needs of young adults is warranted with several studies already underway.