Accelerometer-determined steps/day and metabolic syndrome

Joint Association of Change in Physical Activity and Sitting Time with Metabolic Syndrome Risk: A Prospective Cohort Study

Background and Aims: The purpose of this study was to investigate the combined impact of variations in physical activity (PA) and sitting time (ST) on the risk of developing metabolic syndrome (MetS). Methods: This study was conducted on a cohort of adults from the general population, aged 40-69 years, who participated in the KOGES community-based cohort study over a span of 10 years. Changes in PA and ST were assessed using the results from PA questionnaires completed during baseline and follow-up surveys. The diagnosis of MetS was determined according to the criteria established by the International Diabetes Federation. To evaluate the combined effect of PA and ST changes on the incidence of MetS, we calculated hazard ratios and 95% confidence intervals using a Cox proportional hazards regression model. Result: The incidence of MetS was reduced by 39% (HR = 0.61, 95% CI = 0.46-0.82) for increased ST/increased PA and 26% (HR = 0.74, 95% CI = 0.58-0.94) for decreased ST/increased PA, compared with increased ST/decreased PA, respectively. In addition, this study confirmed that the combined impact of changes in PA and ST, based on the domain of PA, on the incidence of MetS varied. Conclusion: Changes in ST and PA are associated with the risk of developing MetS. These findings lay the groundwork for further research on the relationship between changes in PA, ST, and the occurrence of diseases.

Relationship between Change in Physical Activity and Risk of Metabolic Syndrome: A Prospective Cohort Study

Background

This study investigates the relationship between changes in physical activity levels and risk of metabolic syndrome.

Methods

This study examined 1,686 adults aged 40 to 69 years from a community-based cohort study with complete 1st to 4th follow-up data between 2011 and 2020. Changes in physical activity were evaluated through baseline and follow-up surveys using physical activity questionnaires. Metabolic syndrome was diagnosed according to the International Diabetes Federation criteria. A survival analysis was conducted using a multivariate extended Cox regression model with a significance level set at P<0.05.

Results

Participants were divided into groups according to physical activity levels. The newly inactive group (vigorous physical activity ≤150 minutes at first follow-up) had a 36% increase in the hazard ratio (HR) for metabolic syndrome compared with the consistently inactive group (≤150 minutes at both baseline and first follow-up) (HR, 1.36; 95% confidence interval [CI], 1.04 to 1.79). The newly active group (walking ≤420 minutes per week at baseline and >420 minutes per week at first follow-up) had a 25% decrease in the HR for metabolic syndrome compared with the consistently inactive group (walking ≤420 minutes per week at both baseline and first follow-up) (HR, 0.75; 95% CI, 0.57 to 0.98).

Conclusion

Changes in physical activity levels are associated with risk of metabolic syndrome. These results provide important insights for future investigations into the link between physical activity changes and disease occurrence.

Influence of Central Obesity on Associations Between Physical Activity, Sitting Time, and Metabolic Syndrome Among Middle-Aged and Older Adults in Urban China: A Cross-Sectional Study

Objective

This study assessed possible associations among physical activity (PA), sitting time (ST), metabolic syndrome (MetS), and the individual components thereof. We analyzed the entire study sample and subpopulations stratified by visceral fat area (VFA). We hypothesized that individuals with elevated VFA might respond differently to modifiers of metabolic health, including PA and ST.

Methods

This cross-sectional study, conducted between March and May 2010, enrolled 957 adults with abdominal magnetic resonance imaging (MRI) aged 40-65 years living in the urban communities in Hangzhou, China. PA and ST were recorded using the standard International Physical Activity Questionnaire (IPAQ) and categorized into three levels. The ethnicity-specific cutoff for central obesity was VFA ≥ 80 cm2 on MRI according to Chinese population-based research. Multiple logistic regression models were used to analyze the associations between PA, ST, MetS and its components.

Results

In the total subject population, participants reporting high level of PA were at a lower risk of MetS (OR = 0.46, 95% CI: 0.25, 0.86) than those declaring low PA. In the subgroup population with VFA ≥ 80 cm2 (ie, with central obesity), moderate-to-high PA levels were associated with a lower risk of MetS (p for trend < 0.05) and a lower risk of decreased high-density lipoprotein cholesterol (HDL-C) concentrations (p for trend < 0.05). In addition, ST > 3 h/day was a risk factor for both MetS (p for trend < 0.05) and hypertriglyceridemia (p for trend < 0.05) in the total subject population. While in the central obesity subgroup, ST > 3 h/day was found a stronger risk factor.

Conclusion

Our study suggests that moderate-to-high levels of PA may have a role in prevention of MetS, and ST > 3 h/day was associated with a higher risk of MetS, particularly in individuals with central obesity.

Parental cardiorespiratory fitness influences early life energetics and metabolic health

High cardiorespiratory fitness (CRF) is associated with a reduced risk of metabolic disease and is linked to superior mitochondrial respiratory function. This study investigated how intrinsic CRF affects bioenergetics and metabolic health in adulthood and early life. Adult rats selectively bred for low and high running capacity [low capacity runners (LCR) and high capacity runners (HCR), respectively] underwent metabolic phenotyping before mating. Weanlings were evaluated at 4-6 wk of age, and whole body energetics and behavior were assessed using metabolic cages. Mitochondrial respiratory function was assessed in permeabilized tissues through high-resolution respirometry. Proteomic signatures of adult and weanling tissues were determined using mass spectrometry. The adult HCR group exhibited lower body mass, improved glucose tolerance, and greater physical activity compared with the LCR group. The adult HCR group demonstrated higher mitochondrial respiratory capacities in the soleus and heart compared with the adult LCR group, which coincided with a greater abundance of proteins involved in lipid catabolism. HCR and LCR weanlings had similar body mass, but HCR weanlings displayed reduced adiposity. In addition, HCR weanlings exhibited better glucose tolerance and higher physical activity levels than LCR weanlings. Higher respiratory capacities were observed in the soleus, heart, and liver tissues of HCR weanlings compared with LCR weanlings, which were not owed to greater mitochondrial content. Proteomic analyses indicated a greater potential for lipid oxidation in the contractile muscles of HCR weanlings. In conclusion, offspring born to parents with high CRF possess an enhanced capacity for lipid catabolism and oxidative phosphorylation, thereby influencing metabolic health. These findings highlight that intrinsic CRF shapes the bioenergetic phenotype with implications for metabolic resilience in early life.NEW & NOTEWORTHY Inherited cardiorespiratory fitness (CRF) influences early life bioenergetics and metabolic health. Higher intrinsic CRF was associated with reduced adiposity and improved glucose tolerance in early life. This metabolic phenotype was accompanied by greater mitochondrial respiratory capacity in skeletal muscle, heart, and liver tissue. Proteomic profiling of these three tissues further revealed potential mechanisms linking inherited CRF to early life metabolism.

Efficacy of an mHealth Behavior Change Intervention for Promoting Physical Activity in the Workplace: Randomized Controlled Trial

BACKGROUND

Insufficient physical activity (PA) is a well-established risk factor for several noncommunicable diseases such as cardiovascular diseases, cancer, diabetes, depression, and dementia. The World Health Organization (WHO) advises that individuals engage in 150 minutes of moderate PA per week or 75 minutes of intense PA per week. According to the WHO's latest report, 23% of adults fail to meet the minimum recommended level of PA. The percentage was even higher in a recent global study that showed 27% of adults were insufficiently active and reported a 5% increase in the prevalence trend of insufficient PA between 2001 and 2016. The study also showed the rate of insufficient PA among countries varied significantly. For instance, it was estimated that 40% were insufficiently active in the United States, and the percentage was even higher in Saudi Arabia (more than 50%). Governments are actively developing policies and methods to successfully establish a PA-inducing environment that encourages a healthy lifestyle in order to address the global steady decline in PA.

OBJECTIVE

The purpose of this study was to determine the effectiveness of mobile health (mHealth) interventions, particularly SMS text messaging interventions, to improve PA and decrease BMI in healthy adults in the workplace.

METHODS

In this parallel, 2-arm randomized controlled trial, healthy adults (N=327) were randomized to receive an mHealth intervention (tailored text messages combined with self-monitoring (intervention; n=166) or no intervention (control; n=161). Adults who were fully employed in an academic institution and had limited PA during working hours were recruited for the study. Outcomes, such as PA and BMI, were assessed at baseline and 3 months later.

RESULTS

Results showed significant improvement in PA levels (weekly step counts) in the intervention group (β=1097, 95% CI 922-1272, P<.001). There was also a significant reduction in BMI (β=0.60, 95% CI 0.50-0.69, P<.001).

CONCLUSIONS

Combining tailored text messages and self-monitoring interventions to improve PA and lower BMI was significantly effective and has the potential to leverage current methods to improve wellness among the public.

Validity and Accuracy of Step Count as an Indicator of a Sedentary Lifestyle in People With Chronic Obstructive Pulmonary Disease

OBJECTIVE

To determine the validity and accuracy of <5000 steps/day as a sedentary lifestyle indicator, and the optimal step count cut point value for indicating a sedentary lifestyle in people with chronic obstructive pulmonary disease (COPD).

DESIGN

Analysis of baseline data from a randomized clinical trial.

SETTING

Sydney, Australia.

PARTICIPANTS

Stable COPD on the waitlist for pulmonary rehabilitation.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Step count and time in sedentary behavior (SB) were assessed using thigh-worn accelerometry. A sedentary lifestyle was defined as <5000 steps/day. Pearson correlation coefficients were analyzed between step count and time spent in SB. Sensitivity, specificity, and accuracy were calculated for the <5000 steps/day threshold. Receiver operating characteristic curves with the area under the curve were computed for step count in identifying a sedentary lifestyle.

RESULTS

69 people with COPD (mean age=74 years, SD=9; forced expiratory volume in 1 second, mean=55%, SD=19 predicted) had sufficient wear data for analysis. There was a moderate inverse correlation between step count and time spent in SB (r=-0.58, P<.001). Step count had a fair discriminative ability for identifying a sedentary lifestyle (area under the curve=0.80, 95% confidence interval [CI], 0.68-0.91). The <5000 steps/day threshold had a sensitivity, specificity, and accuracy of 82% (95% CI, 70-94), 70% (95% CI, 54-86), and 78%, respectively. A lower threshold of <4300 steps/day was more accurate for ruling in a sedentary lifestyle.

CONCLUSIONS

Compared with thigh-worn accelerometry, <5000 steps/day is a valid and reasonably accurate indicator of a sedentary lifestyle in this population.

Identifying the Optimal Parameters to Express the Capacity-Activity Interrelationship of Community-Dwelling Older Adults Using Wearable Sensors

Mobility is the primary indicator of quality of life among older adults. Physical capacity (PC) and physical activity (PA) are two determinants of mobility; however, PC and PA are complex constructs represented by numerous parameters. This research sought to identify the optimal parameters that may be used to represent PC and PA of older adults, while exploring the interrelationship of these two constructs. Participants were 76 community-dwelling older adults (M age = 74.05 ± 5.15 yrs.). The McRoberts MoveTest was used to objectively measure PC in the laboratory with the following tests: the Short Physical Performance Battery, the Sway test, Sit to Stands, and the Timed Up and Go. PA was then measured at home for one week using the McRoberts USB Dynaport. Correlation analyses resulted in 55% and 65% reductions of PC and PA parameters, respectively. Clustering identified five representative PC parameters and five representative PA parameters. Canonical correlation analysis identified a non-significant correlation between the two sets of parameters. A novel approach was used to define PC and PA by systematically reducing these constructs into representative parameters that provide clinically relevant information, suggesting that they are an accurate representation of one's PC and PA. A non-significant correlation between PC and PA suggests that there is no relationship between the two in this sample of community-dwelling older adults. The research provided insight into two important determinants of older adult mobility, and how they influence each other.

The evolution of human step counts and its association with the risk of chronic disease

Walking - humans' most fundamental form of moderate intensity physical activity - is associated with reduced risks of morbidity and mortality. Evolutionary perspectives have contributed much to understanding the effects of walking and other physical activities on health; however, we know comparatively little about how step counts (steps taken per day) changed over the course of human evolution, potentially affecting how selection operated on physiological responses to moderate intensity physical activity that influence morbidity and mortality. Here, we compare step counts across humans and our closest living relatives, the great apes. Compiling data from epidemiology and comparative physiology, we show how step counts more than tripled during human evolution, potentially linking higher levels of moderate intensity physical activity with reduced morbidity and mortality, and we highlight how recent decreases in step counts are an evolutionary mismatch. We raise the hypothesis that the dose-response relationship between moderate intensity physical activity and health was shifted in humans to require more steps per day to promote extended healthspan and lifespan.

Association of accelerometer-derived step volume and intensity with hospitalizations and mortality in older adults: A prospective cohort study

PURPOSE

This study aimed to examine the associations of accelerometer-derived steps volume and intensity with hospitalizations and all-cause mortality in older adults.

METHODS

This prospective cohort study involved 768 community-dwelling Spanish older adults (78.8 ± 4.9 years, mean ± SD; 53.9% females) from the Toledo Study for Healthy Aging (2012-2017). The number of steps per day and step cadence (steps/min) were derived from a hip-mounted accelerometer worn for at least 4 days at baseline. Participants were followed-up over a mean period of 3.1 years for hospitalization and 5.7 years for all-cause mortality. Cox proportional hazards regression models were used to estimate the individual and joint associations between daily steps and stepping intensity with hospitalizations and all-cause mortality.

RESULTS

Included participants walked 5835 ± 3445 steps/day with an intensity of 7.3 ± 4.1 steps/min. After adjusting for age, sex, body mass index (BMI), education, income, marital status and comorbidities, higher step count (hazard ratio (HR) = 0.95, 95% confidence interval (95%CI: 0.90-1.00, and HR = 0.87, 95%CI: 0.81-0.95 per additional 1000 steps) and higher step intensity (HR = 0.95, 95%CI: 0.91-0.99, and HR = 0.89, 95%CI: 0.84-0.95 per each additional step/min) were associated with fewer hospitalizations and all-cause mortality risk, respectively. Compared to the group having low step volume and intensity, individuals in the group having high step volume and intensity had a lower risk of hospitalization (HR = 0.72, 95%CI: 0.52-0.98) and all-cause mortality (HR = 0.60, 95%CI: 0.37-0.98).

CONCLUSION

Among older adults, both high step volume and step intensity were significantly associated with lower hospitalization and all-cause mortality risk. Increasing step volume and intensity may benefit older people.

The Effect of a Future-Self Avatar Mobile Health Intervention (FutureMe) on Physical Activity and Food Purchases: Randomized Controlled Trial

BACKGROUND

Insufficient physical activity and unhealthy diets are contributing to the rise in noncommunicable diseases. Preventative mobile health (mHealth) interventions may help reverse this trend, but present bias might reduce their effectiveness. Future-self avatar interventions have resulted in behavior change in related fields, yet evidence of whether such interventions can change health behavior is lacking.

OBJECTIVE

We aimed to investigate the impact of a future-self avatar mHealth intervention on physical activity and food purchasing behavior and examine the feasibility of a novel automated nutrition tracking system. We also aimed to understand how this intervention impacts related attitudinal and motivational constructs.

METHODS

We conducted a 12-week parallel randomized controlled trial (RCT), followed by semistructured interviews. German-speaking smartphone users aged ≥18 years living in Switzerland and using at least one of the two leading Swiss grocery loyalty cards, were recruited for the trial. Data were collected from November 2020 to April 2021. The intervention group received the FutureMe intervention, a physical activity and food purchase tracking mobile phone app that uses a future-self avatar as the primary interface and provides participants with personalized food basket analysis and shopping tips. The control group received a conventional text- and graphic-based primary interface intervention. We pioneered a novel system to track nutrition by leveraging digital receipts from loyalty card data and analyzing food purchases in a fully automated way. Data were consolidated in 4-week intervals, and nonparametric tests were conducted to test for within- and between-group differences.

RESULTS

We recruited 167 participants, and 95 eligible participants were randomized into either the intervention (n=42) or control group (n=53). The median age was 44 years (IQR 19), and the gender ratio was balanced (female 52/95, 55%). Attrition was unexpectedly high with only 30 participants completing the intervention, negatively impacting the statistical power. The FutureMe intervention led to small statistically insignificant increases in physical activity (median +242 steps/day) and small insignificant improvements in the nutritional quality of food purchases (median -1.28 British Food Standards Agency Nutrient Profiling System Dietary Index points) at the end of the intervention. Intrinsic motivation significantly increased (P=.03) in the FutureMe group, but decreased in the control group. Outcome expectancy directionally increased in the FutureMe group, but decreased in the control group. Leveraging loyalty card data to track the nutritional quality of food purchases was found to be a feasible and accepted fully automated nutrition tracking system.

CONCLUSIONS

Preventative future-self avatar mHealth interventions promise to encourage improvements in physical activity and food purchasing behavior in healthy population groups. A full-powered RCT is needed to confirm this preliminary evidence and to investigate how future-self avatars might be modified to reduce attrition, overcome present bias, and promote sustainable behavior change.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04505124; https://clinicaltrials.gov/ct2/show/NCT04505124.

Prevalence of Metabolic Syndrome and Association with Physical Activity and Frailty Status in Spanish Older Adults with Decreased Functional Capacity: A Cross-Sectional Study

Metabolic syndrome (MetS) is a cluster of medical conditions associated with several health disorders. MetS and frailty can be related to prolonged physical deconditioning. There is a need to know whether there is concordance between the different ways of diagnosing it and to know their prevalence in Spanish older adults. Thus, the aims of this study were to describe the prevalence of MetS; to analyse the concordance between different definitions to diagnose MetS; and to study the associations between MetS, frailty status, and physical activity (PA) in older adults with decreased functional capacity. This report is a cross-sectional study involving 110 Spanish older adults of ages ≥65 years with decreased functional capacity. Clinical criteria to diagnose MetS was defined by different expert groups. Anthropometric measurements, blood biochemical analysis, frailty status, functional capacity, and PA were assessed. The Kappa statistic was used to determine the agreement between the five MetS definitions used. Student’s t-test and the Pearson chi-square test were used to examine differences between sex, frailty, and PA groups. The sex-adjusted prevalence of MetS assessed by the National Cholesterol Education Program—Third Adult Treatment Panel was 39.4% in men and 32.5% in women. The International Diabetes Federation and the Harmonized definitions had the best agreement (k = 1.000). The highest odds ratios (ORs) of cardiometabolic risk factors to develop MetS were elevated triglycerides (37.5) and reduced high-density lipoprotein cholesterol (27.3). Central obesity and hypertension prevalence were significantly higher in the non-active group (70.7% and 26.8%, respectively), compared to the active group (50.0% and 7.7%, respectively). Moreover, the active group (OR = 0.85, 95% CI = 0.35, 2.04) and active women group (OR = 0.77, 95% CI = 0.27, 2.20) appeared to show a lower risk of developing this syndrome. MetS is highly prevalent in this sample and changes according to the definition used. It seems that sex and frailty do not influence the development of MetS. However, PA appears to decrease central obesity, hypertension, and the risk of developing MetS.

The relationship between moderate to vigorous physical activity and metabolic syndrome: a Bayesian measurement error approach

Metabolic Syndrome (MetS) is a serious condition that can be an early warning sign of heart disease and Type 2 diabetes. MetS is characterized by having elevated levels of blood pressure, cholesterol, waist circumference, and fasting glucose. There are many articles in the literature exploring the relationship between physical activity and MetS, but most do not consider the measurement error in the physical activity measurements nor the correlations among the MetS risk factors. Furthermore, previous work has generally treated MetS as binary, rather than directly modeling the risk factors on their measured, continuous space. Using data from the National Health and Nutrition Examination Survey (NHANES), we explore the relationship between minutes of moderate to vigorous physical activity (MVPA) and MetS risk factors. We construct a measurement error model for the accelerometry data, and then model its relationship between MetS risk factors with nonlinear seemingly unrelated regressions, incorporating dependence among MetS risk factors. The novel features of this model give the medical research community a new way to understand relationships between MVPA and MetS. The results of this approach present the field with a different modeling perspective than previously taken and suggest future avenues of scientific discovery.

The Effect of Wearable and Smartphone Applications on Physical Activity, Quality of Life, and Cardiovascular Health Outcomes in Overweight/Obese Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Advances in the device and smartphone technology have resulted in a convenient option for providing physical activity strategies; this is especially important during the coronavirus disease 2019 pandemic.

OBJECTIVE

The purpose of this meta-analysis is to evaluate the efficacy of wearable and smartphone-based interventions to promote physical activity and improve quality of life and cardiovascular health outcomes among overweight/obese adults.

DATA SOURCES

We searched relevant databases up to 18 November 2021 for conducting a systematic review and meta-analysis of randomized controlled trials lasting 4 or more weeks that investigated the impacts of wearables and smartphone applications on physical activity, quality of life and health outcomes.

RESULTS

Twenty-six studies including 2373 participants were included. There was a significant pooled standard mean differences (SMD) for the comparison between intervention versus control in steps per day (SMD: 0.54; p = 0.0003), moderate-to-vigorous physical activity (SMD: 0.47; p = 0.02), quality of life (SMD: 0.33; p = 0.0006), body weight (mean difference (MD), -1.61 kg; p = 0.009), and BMI (MD, -0.59 kg/m²; p = 0.04). There were no significant differences between the intervention and control groups for systolic and diastolic blood pressure and resting heart rate (all p > 0.05).

CONCLUSION

Our findings suggest that wearable and smartphone-based interventions are effective strategies in promoting physical activity and can provide a direct contact line to health professionals.

Effect of Walking Steps Measured by a Wearable Activity Tracker on Improving Components of Metabolic Syndrome: A Prospective Study

We compared the improvement in components of metabolic syndrome (MS) before and after lifestyle modification, as determined by daily step counts (on a wrist-worn Fitbit®) in participants with and without MS recruited from volunteers attending medical health checkup programs. A linear mixed model was used to analyze the change in MS components between participants with and without MS by group × time interaction. Multiple logistic regression analysis after adjustment for confounders was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) for improvements in MS components per 1000-steps/day increments. Waist circumference, triglycerides, fasting plasma glucose, and diastolic blood pressure were significantly different between participants with and without MS (group × time: p = 0.010, p < 0.001, p = 0.025, and p = 0.010, respectively). Multivariable-adjusted ORs (95% CI) of improvement in MS components per 1000-steps/day increments were 1.24 (1.01−1.53) in participants with and 1.14 (0.93−1.40) in participants without MS. Walking improved MS components more in individuals with than without MS. From a public health perspective, walking should be encouraged for high-risk MS individuals.

Acceptability and feasibility of an online physical activity program for women over 50: a pilot trial

Regular physical activity benefits health across the lifespan. Women in middle-age often juggle carer and work responsibilities, are often inactive, and may benefit from tailored support to increase physical activity. Establish the acceptability, feasibility, and impact on physical activity of a scalable program for women 50+ years. This pilot trial randomized participants to immediate program access, or to a wait-list control. [Active Women over 50 Online] program included: (1) study-specific website, (2) 8 emails or 24 SMS motivation-based messages, (3) one telephone health-coaching session. Outcomes, at 3 months, were acceptability (recommend study participation, intervention uptake), feasibility (recruitment, reach, completion), intervention impact (physical activity), intervention impressions. At baseline, 62 participants of mean (SD) age 59 (±7) years took 7459 (±2424) steps/day and most (92%) reported ≥2 medical conditions. At 3 months, acceptability and impact data were available for 52 (84%) and 57 (92%) participants, respectively. Study participation was recommended by 83% of participants. Participants mostly agreed to receive health coaching (81%) and messages (87%: email = 56%, SMS = 44%), opened 82% of emails and accessed the website 4.8 times on average. Respondents reported the intervention supported their physical activity. Intervention participants were more likely to increase steps from baseline by 2000+/day (OR: 6.31, 95% CI: 1.22 to 32.70, p = .028) than controls, and trended toward more light-intensity (p = .075) and moderate-vigorous intensity physical activity (p = .11). The [Active Women over 50 Online] program demonstrated acceptability and feasibility among the target population, and effectiveness in some domains in the short term. Results warrant further testing in a full-scale RCT.

Relationship between metabolic syndrome and moderate-to-vigorous physical activity among adults 18 years old and over

The prevalence of metabolic syndrome (MetS) risk factors among the Korean population requires effective health surveillance and examination of the effects of preventative behaviors. Thus, the objective of this study is to evaluate the relationships between the clustering of MetS and MVPA in a large sample of 36,987 Koreans ranging from 20 to 80 years of age. This study recruited a total of 36,987 adults (23,813 males and 13,174 females). All participants were assessed for moderate-to-vigorous physical activity (MVPA) using the Korean version short form of the International Physical Activity Questionnaire (IPAQ). The International Diabetes Federation and the Adult Treatment Panel III criteria for blood pressure, hyperglycemia, low high-density lipoprotein cholesterol (HDL-C), and high triglycerides (TG) defined MetS. Waist circumference (WC) was determined by Asian-Pacific region populations. According to the 150-minute MVPA, there were differences in MetS risk factors in young adult males, and only three factors (WC, HDL-C, and TG) were different males in ≥ 70 years old. In females, there was a difference in MetS risk factors in the elderly, and only three factors (WC, blood pressure, and TG) were different females in ≤ 29 years old. The males who did not met the recommended MVPA had a 1.16 to 3.14 -times increase in the MetS risk factors. The females who did not met the recommended MVPA had a 1.18 to 2.57 -times increase in the MetS risk factors. Our study provides evidence that Korean adults who do not engage in recommended MVPA levels increase the odds ratio for each of the MetS risk factors when compared to those who meet the recommendations.

A quality-improvement optimization pilot of BariFit, a mobile health intervention to promote physical activity after bariatric surgery

Bariatric surgery is the most effective treatment for severe obesity (body mass index >40), helping individuals lose, on average, 25%-29% of their body weight over the first year. However, many patients begin to plateau and regain weight within 12-24 months, and 20% of patients begin to regain weight within 6 months postsurgery. As physical activity (PA) is an important predictor of weight loss and maintenance postsurgery, there is a need for scalable, effective lifestyle interventions to help bariatric patients increase PA in order to maximize their weight loss and maintenance. To assess feasibility of using mobile health (mHealth) tools to support PA postsurgery, we conducted a quality-improvement optimization pilot of BariFit, an mHealth intervention that combines commercial devices and custom text messages. Fifty-one bariatric patients enrolled in a 16-week optimization pilot of BariFit. To assess feasibility, pre-post changes in PA were assessed using activPAL. In addition, the pilot randomized, using a 2 × 2 factorial design, two adaptive approaches to daily step goals (variable and 60th percentile goals) and provision of rest days (yes/no), and microrandomized provision of SMS-delivered activity suggestions five times a day for each participant. Adherence to using study equipment was over 95% at 16 weeks. Participants increased PA by 1,866 steps from baseline to end-of-study (p < .007). Participants who received variable step goals averaged 1,141 more steps per day (p = .096) than those who received 60th percentile goals. Activity suggestions had no effect. mHealth interventions are feasible for supporting PA postbariatric surgery.

Using Step Counts to Prescribe Physical Activity: What Is the Optimal Dose?

ABSTRACT

An activity goal of 10,000 steps per day is widely known but was not initially developed based on scientific evidence. The last several years have seen an increase in both the availability of consumer-based step counting devices and research examining the link between daily step counts and various health outcomes. Daily step counts are an intuitive metric of physical activity and are useful for goal-setting and motivating behavioral change. This article reviews the current evidence for daily step counts as related to common health conditions to determine activity goals to prescribe to patients, and also discusses factors to consider when counseling patients on physical activity.

Long-term Effectiveness of mHealth Physical Activity Interventions: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Mobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood.

OBJECTIVE

The primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators.

METHODS

We performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool.

RESULTS

Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence.

CONCLUSIONS

mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects.

Predicting lying, sitting, walking and running using Apple Watch and Fitbit data

OBJECTIVES

This study's objective was to examine whether commercial wearable devices could accurately predict lying, sitting and varying intensities of walking and running.

METHODS

We recruited a convenience sample of 49 participants (23 men and 26 women) to wear three devices, an Apple Watch Series 2, a Fitbit Charge HR2 and iPhone 6S. Participants completed a 65 min protocol consisting of 40 min of total treadmill time and 25 min of sitting or lying time. The study's outcome variables were six movement types: lying, sitting, walking self-paced and walking/running at 3 metabolic equivalents of task (METs), 5 METs and 7 METs. All analyses were conducted at the minute level with heart rate, steps, distance and calories from Apple Watch and Fitbit. These included three different machine learning models: support vector machines, Random Forest and Rotation forest.

RESULTS

Our dataset included 3656 and 2608 min of Apple Watch and Fitbit data, respectively. Rotation Forest models had the highest classification accuracies for Apple Watch at 82.6%, and Random Forest models had the highest accuracy for Fitbit at 90.8%. Classification accuracies for Apple Watch data ranged from 72.6% for sitting to 89.0% for 7 METs. For Fitbit, accuracies varied between 86.2% for sitting to 92.6% for 7 METs.

CONCLUSION

This preliminary study demonstrated that data from commercial wearable devices could predict movement types with reasonable accuracy. More research is needed, but these methods are a proof of concept for movement type classification at the population level using commercial wearable device data.

Associations of Light, Moderate to Vigorous, and Total Physical Activity With the Prevalence of Metabolic Syndrome in 4,652 Community-Dwelling 70-Year-Olds: A Population-Based Cross-Sectional Study

In this cross-sectional study, the authors investigated the associations of objectively measured physical activity (PA) with the prevalence of metabolic syndrome (MetS) in older adults. Accelerometer-derived light-intensity PA, moderate to vigorous PA, and steps per day were measured in (N = 4,652) 70-year-olds in Umeå, Sweden, during May 2012-November 2019. The MetS was assessed according to the American Heart Association/ National Heart, Lung and Blood Institute criteria. The prevalence of MetS was 49.3%. Compared with the reference, the odds ratios for MetS in increasing quartiles of light-intensity PA were 0.91 (0.77-1.09), 0.75 (0.62-0.89), and 0.66 (0.54-0.80). For moderate to vigorous PA, the corresponding odds ratios were 0.79 (0.66-0.94), 0.67 (0.56-0.80), and 0.56 (0.46-0.67). For steps per day, the odds ratios were 0.65 (0.55-0.78), 0.55 (0.46-0.65), and 0.45 (0.36-0.55). In summary, this study shows that greater amounts of PA, regardless of intensity, are associated with lower odds of MetS. With the limitation of being an observational study, these findings may have implications for the prevention of MetS in older adults.

Does physical activity lower the risk for metabolic syndrome: a longitudinal study of physically active older women

Background

The associations between physical activity and metabolic syndrome (MetS) have been mainly found in cross-sectional studies. The aim of this longitudinal study was to examine the relationship between meeting step-based guidelines and changes in the risk of metabolic syndrome.

Methods

This study included data from older women (baseline age 62.9 ± 4.3 years) from a 7-year longitudinal study in Central Europe. At baseline and follow-up, physical activity was measured by an accelerometer, and the risk for MetS was assessed according to the NCEP-ATP III criteria. In 59 women, multivariate repeated measures ANOVA was used to compare differences in changes in the risk of MetS in groups based on meeting step-based guidelines (10,000 steps/day and 9000 steps/day for women aged <65 and ≥ 65 years, respectively).

Results

Over 7 years, steps/day increased from 10,944 ± 3560 to 11,652 ± 4865, and the risk of MetS decreased from 41 to 12% in our sample. Women who longitudinally met step-based guidelines had a significantly higher mean concentration of high-density cholesterol (HDL-C) (64.5 and 80.3 mg/dL at baseline and follow-up, respectively) and a lower concentration of triglycerides (TGs) (158.3 and 123.8 mg/dL at baseline and follow-up, respectively) at follow-up compared to baseline. Moreover, women who increased their daily steps over 7 years to the recommended steps/day value significantly decreased the concentration of TGs (158.3 mg/dL and 123.8 mg/dL at baseline and follow-up, respectively).

Conclusions

Our study might suggest that the long-term meeting of step-based guidelines or an increase in daily steps/day to achieve the recommended value could be related to a lower risk of MetS, specifically in concentrations of HDL-C and TG. These findings may help in designing interventions aiming to decrease the risk of MetS in older women.

Validity of a Smart-Glasses-Based Step-Count Measure during Simulated Free-Living Conditions

Step counting represents a valuable approach to monitor the amount of daily physical activity. The feet, wrist and trunk have been demonstrated as the ideal locations to automatically detect the number of steps through body-worn devices (i.e., step counters). Key features of such devices are high usability, practicality and unobtrusiveness. Therefore, the opportunity to integrate step-counting functions in daily worn accessories represents one of the recent and most important challenges. In this context, the present study aimed to investigate the validity of a smart-glasses-based step-counter measure by comparing their performances against the most popular commercial step counters. To this purpose, smart glasses data from 26 healthy subjects performing simulated free-living walking conditions along a predefined path were collected. Reference measures from inertial sensors mounted on the subjects’ ankles and data from commercial (waist- and wrists-worn) step counters were acquired during the tests. The results showed an overall percentage error of 1%. In conclusion, the proposed smart glasses could be considered an accurate step counter, showing performances comparable to the most common commercial step counters.

Setting performance and learning goals is useful for active and inactive individuals, if goals are personalized and flexible: commentary on Swann et al. (2020)

This commentary expands on the recent critical review by Swann et al. (2020) which aimed to update the applications of Goal-Setting Theory (Locke & Latham, 2019) in physical activity promotion. Drawing from other work on goal striving and behaviour change, we make four key points to further elaborate on Swann et al.'s review. First, goals are more likely to be enacted if they are specific, personally relevant and pursued for autonomous motives; performance goals can be useful for inactive individuals if set appropriately and self-endorsed. Second, goal striving needs to be flexible and adjustable, and to consider goal priorities and time factors relevant to goal engagement and disengagement. Goal-Setting Theory would therefore benefit from being expanded to add the factors of goal priority, context, and time. Third, research on goal setting in physical activity could benefit from embracing idiographic designs and interventions. Fourth, other theoretical approaches to goal striving should be considered when discussing goal setting in physical activity promotion.

Physical activity levels in American and Japanese men from the ERA-JUMP Study and associations with metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS) is a global health problem. Physical activity (PA) is a known modifiable risk factor for MetS and individual MetS components. However, the role of PA could differ between sub-populations due to differences in the variability of PA and other MetS risk factors. To examine these differences, multi-country studies with standardized outcome measurement methods across cohorts are needed.

METHODS

Cross-sectional PA levels (total and domain specific) in healthy middle-aged (44-56 years) men in the Risk Factor Assessment among Japanese and U.S. Men in the Post-World War II Birth Cohort (ERA-JUMP) Study (n = 730; American: n = 417; Japanese: n = 313; from population-representative samples in Pittsburgh, Pennsylvania, USA, and Kusatsu, Shiga, Japan) were compared. The relationships between PA levels and MetS (overall and specific components) in/across the American and Japanese sub-cohorts (adjusting for age, smoking, and alcohol consumption) were also assessed using the same instruments (pedometer and validated questionnaire) to measure PA in both cohorts.

RESULTS

A total of 510 individuals provided complete data on PA (American: n = 265; Japanese: n = 245). The American cohort had significantly lower mean ± SD steps/day (7878 ± 3399 steps/day) vs. the Japanese cohort (9055 ± 3797 steps/day) (p < 0.001) but had significantly higher self-reported moderate-vigorous leisure PA (American: 15.9 (7.4-30.3) metabolic task equivalent hours per week (MET-h/week) vs. Japanese: 4.0 (0-11.3) MET-h/week, p < 0.0001). In both sub-cohorts, each 1000 steps/day increase was associated with lower odds of having MetS (American: OR = 0.90, 95%CI: 0.83-0.98; Japanese: OR = 0.87, 95%CI: 0.79-0.95) and the individual MetS component of high waist circumference (American: OR = 0.86, 95%CI: 0.79-0.94; Japanese: OR = 0.87, 95%CI: 0.80-0.95). In the American cohort only, higher self-reported leisure PA (Met-h/week) was associated with lower odds of MetS and high waist circumference (OR = 0.98, 95%CI: 0.97-0.99 for MetS and waist circumference, respectively).

CONCLUSION

Higher total step counts/day had an important protective effect on MetS prevalence in both the Japanese and American cohorts, despite differences in PA levels and other MetS risk factors. The effect of steps/day (across all intensity levels) was much greater than domain-specific moderate-vigorous PA captured by questionnaire, suggesting the need for measurement tools that can best capture total movement when examining the effects of PA on MetS development.

How Many Steps Per Day are Necessary to Prevent Postoperative Complications Following Hepato-Pancreato-Biliary Surgeries for Malignancy?

PURPOSE

The current study was designed to investigate the association between the average preoperative physical activity and postoperative outcomes in patients undergoing surgeries for hepato-pancreato-biliary (HPB) malignancy.

METHODS

Patients who were scheduled to undergo open abdominal surgeries for HPB malignancies (major hepatectomy, pancreatoduodenectomy, or hepato-pancreatoduodenectomy) between 2016 and 2017 were included. The average steps per day were recorded by a pedometer and calculated for each patient during the preoperative waiting period. Physical activity levels were classified according to the average number of daily steps as poor (< 5000 steps/day) and good (≥ 5000 steps/day).

RESULTS

Of the 105 eligible patients, 78 met the inclusion criteria. The median number of steps per day was 6174. There were 48 patients (62%) with good physical activity and 30 patients (38%) with poor physical activity. Patients with poor physical activity revealed a significantly higher rate of major complications with Clavien grade ≥ 3 (63% vs. 35%, p = 0.016), a higher rate of infectious complications (53% vs. 23%, p = 0.006), and a longer postoperative hospital stay (median, 30 vs. 21 days, p < 0.001) compared with those with good physical activity. After a multivariate analysis, poor physical activity was identified as an independent risk factor for the development of major complications (odds ratio, 2.842, p = 0.042) and infectious complications (odds ratio, 3.844, p = 0.007).

CONCLUSIONS

The current study demonstrated that preoperative physical activity levels are associated with the incidence of major postoperative complications following HPB surgery for malignancy.

Is the goal of 12,000 steps per day sufficient for improving body composition and metabolic syndrome? The necessity of combining exercise intensity: a randomized controlled trial

Background

To investigate the differences in body composition and metabolic syndrome (MS) under a daily 12,000-step strategy with or without moderate-intensity walking exercise in college students with obesity.

Methods

Thirty-two adults with obesity (mean (s.d.) age: 19.72 (0.80) years; height: 165.38 (3.99) cm; wt: 83.31 (4.66) kg; body mass index: 30.38 (0.83) kg m^− 2) were recruited and randomly assigned to the walking step goal group (WSG; achieving 12,000 steps per day), walking exercise group (WEG; achieving 12,000 steps per day, including 3 days per week on which walking at a step rate of over 103 steps min^− 1 was required), or control group (CG; maintaining a free-living life style). Each participant’s accumulated daily steps from daily activities and walking exercises were monitored using a smartwatch for 8 weeks. The variables of body composition and MS were measured before and after intervention.

Results

Average daily steps over 8 weeks did not significantly differ between the WSG and WEG (11,677.67 (480.24) vs. 12,131.90 (527.14) steps per day, respectively, P > .05). Although the CG and WSG showed no improvement in body composition, the WEG exhibited significant improvements in terms of hip circumference and visceral fat area (VFA) (∆ − 2.28 (3.27) cm and ∆ − 13.11 (9.83) cm², respectively, P < .05); high-density lipoprotein cholesterol (HDL-C), fasting glucose (FG), and triglycerides (TG) (∆ 16.36 (8.39), ∆ − 2.53 (3.73), and ∆ − 10.52 (36.26) mg dL^− 1, respectively, P < .05). The WSG exhibited improvements only in HDL-C (∆ 14.24 (16.13) mg dL^− 1, P < .05).

Conclusion

The combination of walking exercise program and daily step goal is a more time efficient strategy in improving body composition and MS than simply establishing a daily step goal. Furthermore, this strategy may also include a potential reduction effect on the risk factors of cardiovascular diseases.

Trial registration

Australian New Zealand Clinical Trials Registry, number ACTRN12618001237279 (Retrospectively registered).

Cardiometabolic thresholds for peak 30-min cadence and steps/day

PURPOSE

To provide empirically-supported thresholds for step-based intensity (i.e., peak 30-min cadence; average of the top 30 steps/min in a day) and steps/day in relation to cardiometabolic health outcomes.

METHODS

Receiver operating characteristic curve analysis was applied to the National Health and Nutrition Examination Survey (NHANES) 2005-2006 accelerometer-derived step data to determine steps/day and peak 30-min cadence as risk screening values (i.e., thresholds) for fasting glucose, body mass index, waist circumference, high blood pressure, triglycerides, and HDL cholesterol. Thresholds for peak 30-min cadence and steps/day were derived that, when exceeded, classify the absence of each cardiometabolic risk factor. Additionally, logistic regression models that included the influence of age and smoking were developed using the sample weights, primary sampling units (PSUs), and stratification variables provided by the NHANES survey. Finally, a decision tree analysis was performed to delineate criteria for at-risk versus healthy populations using cadence bands.

RESULTS

Peak 30-min cadence thresholds across cardiometabolic outcomes ranged from 66-72 steps/min. Steps/day thresholds ranged from 4325-6192 steps/day. Higher thresholds were observed in men compared to women. In men, higher steps/day thresholds were observed in age ranges of 30-39, while in women, higher thresholds were observed in the age-range 50-59 years. Decision trees for classifying being at low risk for metabolic syndrome contained one risk-free leaf at higher cadence bands, specifically for any time accumulated at ≥120 steps/min.

CONCLUSIONS

Minimum thresholds representing absence of cardiometabolic risk range from 4325-6192 steps/day and 66-72 steps/min for peak 30-min cadence. Any time accumulated at ≥120 steps/min was associated with an absence of cardiometabolic risk. Although based on cross-sectional data, these thresholds represent potentially important and clinically interpretable daily physical activity goals.

Physical Activity, Cardiorespiratory Fitness, and the Metabolic Syndrome

Both observational and interventional studies suggest an important role for physical activity and higher fitness in mitigating the metabolic syndrome. Each component of the metabolic syndrome is, to a certain extent, favorably influenced by interventions that include physical activity. Given that the prevalence of the metabolic syndrome and its individual components (particularly obesity and insulin resistance) has increased significantly in recent decades, guidelines from various professional organizations have called for greater efforts to reduce the incidence of this condition and its components. While physical activity interventions that lead to improved fitness cannot be expected to normalize insulin resistance, lipid disorders, or obesity, the combined effect of increasing activity on these risk markers, an improvement in fitness, or both, has been shown to have a major impact on health outcomes related to the metabolic syndrome. Exercise therapy is a cost-effective intervention to both prevent and mitigate the impact of the metabolic syndrome, but it remains underutilized. In the current article, an overview of the effects of physical activity and higher fitness on the metabolic syndrome is provided, along with a discussion of the mechanisms underlying the benefits of being more fit or more physically active in the prevention and treatment of the metabolic syndrome.

Video-Recorded Validation of Wearable Step Counters under Free-living Conditions

PURPOSE

The purpose of this study was to determine the accuracy of 14-step counting methods under free-living conditions.

METHODS

Twelve adults (mean ± SD age, 35 ± 13 yr) wore a chest harness that held a GoPro camera pointed down at the feet during all waking hours for 1 d. The GoPro continuously recorded video of all steps taken throughout the day. Simultaneously, participants wore two StepWatch (SW) devices on each ankle (all programmed with different settings), one activPAL on each thigh, four devices at the waist (Fitbit Zip, Yamax Digi-Walker SW-200, New Lifestyles NL-2000, and ActiGraph GT9X (AG)), and two devices on the dominant and nondominant wrists (Fitbit Charge and AG). The GoPro videos were downloaded to a computer and researchers counted steps using a hand tally device, which served as the criterion method.

RESULTS

The SW devices recorded between 95.3% and 102.8% of actual steps taken throughout the day (P > 0.05). Eleven step counting methods estimated less than 100% of actual steps; Fitbit Zip, Yamax Digi-Walker SW-200, and AG with the moving average vector magnitude algorithm on both wrists recorded 71% to 91% of steps (P > 0.05), whereas the activPAL, New Lifestyles NL-2000, and AG (without low-frequency extension (no-LFE), moving average vector magnitude) worn on the hip, and Fitbit Charge recorded 69% to 84% of steps (P < 0.05). Five methods estimated more than 100% of actual steps; AG (no-LFE) on both wrists recorded 109% to 122% of steps (P > 0.05), whereas the AG (LFE) on both wrists and the hip recorded 128% to 220% of steps (P < 0.05).

CONCLUSIONS

Across all waking hours of 1 d, step counts differ between devices. The SW, regardless of settings, was the most accurate method of counting steps.

Statistical methods to model and evaluate physical activity programs, using step counts: A systematic review

Background

Physical activity reduces the risk of noncommunicable diseases and is therefore an essential component of a healthy lifestyle. Regular engagement in physical activity can produce immediate and long term health benefits. However, physical activity levels are not as high as might be expected. For example, according to the global World Health Organization (WHO) 2017 statistics, more than 80% of the world’s adolescents are insufficiently physically active. In response to this problem, physical activity programs have become popular, with step counts commonly used to measure program performance. Analysing step count data and the statistical modeling of this data is therefore important for evaluating individual and program performance. This study reviews the statistical methods that are used to model and evaluate physical activity programs, using step counts.

Methods

Adhering to PRISMA guidelines, this review systematically searched for relevant journal articles which were published between January 2000 and August 2017 in any of three databases (PubMed, PsycINFO and Web of Science). Only the journal articles which used a statistical model in analysing step counts for a healthy sample of participants, enrolled in an intervention involving physical exercise or a physical activity program, were included in this study. In these programs the activities considered were natural elements of everyday life rather than special activity interventions.

Results

This systematic review was able to identify 78 unique articles describing statistical models for analysing step counts obtained through physical activity programs. General linear models and generalized linear models were the most popular methods used followed by multilevel models, while structural equation modeling was only used for measuring the personal and psychological factors related to step counts. Surprisingly no use was made of time series analysis for analysing step count data. The review also suggested several strategies for the personalisation of physical activity programs.

Conclusions

Overall, it appears that the physical activity levels of people involved in such programs vary across individuals depending on psychosocial, demographic, weather and climatic factors. Statistical models can provide a better understanding of the impact of these factors, allowing for the provision of more personalised physical activity programs, which are expected to produce better immediate and long-term outcomes for participants. It is hoped that this review will identify the statistical methods which are most suitable for this purpose.

Step Counting: A Review of Measurement Considerations and Health-Related Applications

Step counting has long been used as a method of measuring distance. Starting in the mid-1900s, researchers became interested in using steps per day to quantify ambulatory physical activity. This line of research gained momentum after 1995, with the introduction of reasonably accurate spring-levered pedometers with digital displays. Since 2010, the use of accelerometer-based “activity trackers” by private citizens has skyrocketed. Steps have several advantages as a metric for assessing physical activity: they are intuitive, easy to measure, objective, and they represent a fundamental unit of human ambulatory activity. However, since they measure a human behavior, they have inherent biological variability; this means that measurements must be made over 3–7 days to attain valid and reliable estimates. There are many different kinds of step counters, designed to be worn on various sites on the body; all of these devices have strengths and limitations. In cross-sectional studies, strong associations between steps per day and health variables have been documented. Currently, at least eight prospective, longitudinal studies using accelerometers are being conducted that may help to establish dose–response relationships between steps/day and health outcomes. Longitudinal interventions using step counters have shown that they can help inactive individuals to increase by 2500 steps per day. Step counting is useful for surveillance, and studies have been conducted in a number of countries around the world. Future challenges include the need to establish testing protocols and accuracy standards, and to decide upon the best placement sites. These challenges should be addressed in order to achieve harmonization between studies, and to accurately quantify dose–response relationships.

Step-Based Physical Activity Metrics and Cardiometabolic Risk: NHANES 2005-2006

PURPOSE

This study aimed to catalog the relationships between step-based accelerometer metrics indicative of physical activity volume (steps per day, adjusted to a pedometer scale), intensity (mean steps per minute from the highest, not necessarily consecutive, minutes in a day; peak 30-min cadence), and sedentary behavior (percent time at zero cadence relative to wear time; %TZC) and cardiometabolic risk factors.

METHODS

We analyzed data from 3388 participants, 20+ yr old, in the 2005-2006 National Health and Nutrition Examination Survey with ≥1 valid day of accelerometer data and at least some data on weight, body mass index, waist circumference, systolic and diastolic blood pressure, glucose, insulin, HDL cholesterol, triglycerides, and/or glycohemoglobin. Linear trends were evaluated for cardiometabolic variables, adjusted for age and race, across quintiles of steps per day, peak 30-min cadence, and %TZC.

RESULTS

Median steps per day ranged from 2247 to 12,334 steps per day for men and from 1755 to 9824 steps per day for women, and median peak 30-min cadence ranged from 48.1 to 96.0 steps per minute for men and from 40.8 to 96.2 steps per minute for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.001), with increasing quintiles of steps per day and peak 30-min cadence inversely associated with waist circumference, weight, body mass index, and insulin for both men and women. Median %TZC ranged from 17.6% to 51.0% for men and from 19.9% to 47.6% for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.05), with increasing quintiles of %TZC associated with increased waist circumference, weight and insulin for men, and insulin for women.

CONCLUSIONS

This analysis identified strong linear relationships between step-based movement/nonmovement dimensions and cardiometabolic risk factors. These data offer a set of quantified access points for studying the potential dose-response effects of each of these dimensions separately or collectively in longitudinal observational or intervention study designs.

Short-term benefits of an unrestricted-calorie traditional Mediterranean diet, modified with a reduced consumption of carbohydrates at evening, in overweight-obese patients

The Mediterranean diet (MeD) is believed to promote health; nevertheless, changes in the nutritional patterns in the Mediterranean area (increased intake of refined carbohydrates/saturated fats; reduced fibers intake; main calorie load shifted to dinner) led to reduced MeD benefits in recent decades. We retrospectively investigated the effects of a MeD with a low intake of refined carbohydrates in the evening ("MeDLowC") on body weight (BW) and metabolic profile of overweight/obese subjects. According to their adherence to MeDLowC, subjects were classified into 44 (41%) individuals with "excellent" adherence and 63 (59%) with "poor" adherence. Nutritional counseling induced an improvement in BW, glucose metabolism and liver transaminases in both groups, with an increased magnitude of these effects in the "Excellent" adherence group. "Excellent" adherence to MeDLowC improved insulin sensitivity and lipid metabolism. In conclusion, MeD with a restriction of carbohydrates in the evening significantly ameliorates obesity and associated metabolic complications.

Feasibility and acceptance of exercise recommendations (10,000 steps a day) within routine German health check (Check-Up 35/GOÄ29)-study protocol

BACKGROUND

Benefits of exercise to prevent non-communicable diseases are well-documented. Limited data exists to promote physical activity in healthy but sedentary and/or overweight people. Brief interventions within routine German health checks may be an effective way to reach these patients.

METHODS/DESIGN

The quasi-experimental, multi-center prospective feasibility study is designed for general practices in Cologne (intervention group) and Düsseldorf (control group), up to 20 per region. Eight to 10 inactive and/or overweight patients per practice will be recruited for a total of 300. General practitioners and at least one of their nurses for the intervention group will be trained in motivational interviewing and familiarized with low-threshold recommendations for exercise (activities of daily life (ADL), target of 10,000 steps/day) and additional tools (pedometers, activity diaries). Participants in the control group will only receive general advice (150 min of exercise/week). The primary aims are to evaluate the feasibility of this intervention and to determine whether it is possible to reach a mean increase of 1000 steps/day in the target group within 6 months. Secondary objectives focus on the number of patients who reach a target of 10,000 steps/day and their improvements in quality of life and decrease in body mass index, waist circumference, and blood pressure.

DISCUSSION

The study will assess whether it is feasible to run brief interventions within the GP setting can promote an active lifestyle in overweight and/or inactive patients.

Multiple imputation of completely missing repeated measures data within person from a complex sample: application to accelerometer data in the National Health and Nutrition Examination Survey

The Physical Activity Monitor component was introduced into the 2003-2004 National Health and Nutrition Examination Survey (NHANES) to collect objective information on physical activity including both movement intensity counts and ambulatory steps. Because of an error in the accelerometer device initialization process, the steps data were missing for all participants in several primary sampling units, typically a single county or group of contiguous counties, who had intensity count data from their accelerometers. To avoid potential bias and loss in efficiency in estimation and inference involving the steps data, we considered methods to accurately impute the missing values for steps collected in the 2003-2004 NHANES. The objective was to come up with an efficient imputation method that minimized model-based assumptions. We adopted a multiple imputation approach based on additive regression, bootstrapping and predictive mean matching methods. This method fits alternative conditional expectation (ace) models, which use an automated procedure to estimate optimal transformations for both the predictor and response variables. This paper describes the approaches used in this imputation and evaluates the methods by comparing the distributions of the original and the imputed data. A simulation study using the observed data is also conducted as part of the model diagnostics. Finally, some real data analyses are performed to compare the before and after imputation results. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Associations of food consumption, serum vitamins and metabolic syndrome risk with physical activity level in middle-aged adults: the National Health and Nutrition Examination Survey (NHANES) 2005-2006

OBJECTIVE

To examine the associations of food consumption, serum vitamins and metabolic syndrome risk with physical activity level in middle-aged adults.

DESIGN

Cross-sectional.

SETTING

National Health and Nutrition Examination Survey (NHANES) 2005-2006.

SUBJECTS

Adults aged 40-70 years were divided into three groups by tertile of accelerometer-determined steps/d (in men and women, respectively): tertile 1 (sedentary), <6802, <5785; tertile 2 (intermediate), 6802-10698, 5785-9225; tertile 3 (active), ≥10699, ≥9226.

RESULTS

The active men consumed more grain products, fruits and vegetables, whereas the active women consumed more legumes and vegetables, compared with the sedentary group. Serum vitamin concentrations were associated with daily steps in both men and women. Vitamin C, α-carotene, trans-β-carotene, cis-β-carotene, β-cryptoxanthin, lutein+zeaxanthin, lycopene, γ-tocopherol and vitamin D were significantly associated with daily steps. OR (P<0·05) for the sedentary group were 1·52 and 1·61 for low HDL cholesterol, 1·66 and 3·97 for hypertriacylglycerolaemia, 1·02 and 2·73 for abdominal obesity, 1·79 and 1·77 for hyperglycaemia, 1·59 and 1·60 for hypertension, and 1·85 and 2·47 for metabolic syndrome in men and women, respectively.

CONCLUSIONS

Those with the highest steps taken showed a more healthful eating profile and a better serum vitamin profile compared with less active adults. Those with the lowest steps taken had greater odds of having metabolic syndrome and its risk components. Probably, daily walking is a marker of a healthful eating profile and increasing daily walking is one of the healthful ways to decrease the metabolic syndrome and its risk components.

Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults

Daily ambulatory activity is associated with health and functional status in older adults; however, assessment requires multiple days of activity monitoring. The objective of this study was to determine the relative capabilities of self-selected walking speed (SSWS), maximal walking speed (MWS), and walking speed reserve (WSR) to provide insight into daily ambulatory activity (steps per day) in community-dwelling older adults. Sixty-seven older adults completed testing and activity monitoring (age 80.39 [6.73] years). SSWS (R2 = .51), MWS (R2 = .35), and WSR calculated as a ratio (R2 = .06) were significant predictors of daily ambulatory activity in unadjusted linear regression. Cutpoints for participants achieving < 8,000 steps/day were identified for SSWS (≤ 0.97 m/s, 44.2% sensitivity, 95.7% specificity, 10.28 +LR, 0.58 -LR) and MWS (≤ 1.39 m/s, 60.5% sensitivity, 78.3% specificity, 2.79 +LR, 0.50 -LR). SSWS may be a feasible proxy for assessing and monitoring daily ambulatory activity in older adults.

Reduction in pedometer-determined physical activity in the adult Danish population from 2007 to 2012

AIMS

To examine the development in pedometer-determined physical activity from 2007-2008 to 2011-2012 in the adult Danish population.

METHODS

The study population comprised two random samples of 18-75-year-old individuals who took part in cross-sectional studies in 2007-2008 (n=224) and 2011-2012 (n=1515). Pedometer data (sealed Yamax SW 200) were obtained for seven consecutive days. Data for 1624 participants (48.2% men) were included in the analysis. An overall step-defined activity level was examined based on a graduated step index (sedentary, low active, somewhat active, active, highly active). The pedometer-determined outcomes were analysed using regression models.

RESULTS

A borderline significant decline (p=0.077) from 8788 to 8341 steps/day (-446 (95% confidence intervals -50, 943)) was found between 2007-2008 and 2011-2012. Furthermore, a 23.7% (95% confidence intervals -41.7%, -0.1%) lower overall step-defined activity level was observed in 2011-2012 compared to 2007-2008. These changes were primarily due to a reduced level of activity among women. The proportion of individuals taking ⩾10,000 steps/day decreased non-significantly from 34.8% to 29.3%, whereas the proportion taking <5000 steps/day did not differ between survey periods.

CONCLUSIONS

This nationally representative survey suggests an overall reduction in the physical activity level among Danish adults. The reduction was due to a shift in the population distribution from higher to lower levels of activity. If this shift is true, it is worrying from a public health perspective. Our study result needs, however, to be confirmed by other population studies.

Associations Between Physical Activity and Metabolic Syndrome: Comparison Between Self-Report and Accelerometry

PURPOSE

To assess the relationship between self-reported and objectively measured physical activity (PA) and metabolic syndrome and its risk factors in U.S. adults.

DESIGN

A cross-sectional design was used for this study.

SETTING

The study was set among a nationally representative sample of U.S. adults.

SUBJECTS

Adults, ages 20 years and older, from the National Health and Nutrition Examination Survey (NHANES) 2003-2006 (n = 5580) participated in the study.

MEASURES

PA measures included minutes per week of moderate plus vigorous PA estimated by self-report (MVPAsr), total 7-day accelerometry (MVPAa), and accelerometer-based MVPA performed in 10-minute bouts (MVPAb). Risk factors for metabolic syndrome included blood pressure, high-density lipoprotein cholesterol, triglycerides, glucose, and waist circumference.

ANALYSIS

Odds ratios (ORs) for having metabolic syndrome were calculated for men and women who met the Physical Activity Guidelines for Americans compared to those who did not.

RESULTS

Women who did not meet the PA guidelines had significantly greater odds of having metabolic syndrome according to MVPAsr (OR = 2.20; 95% confidence interval [CI] = 1.65-2.94), MVPAa (OR = 4.40; 95% CI = 2.65-7.31), and MVPAb (OR = 2.91; 95% CI = 1.42-5.96). Men had significantly higher odds of having metabolic syndrome according to MVPAa (OR = 2.57; 95% CI = 1.91-3.45) and MVPAb (OR = 2.83; 95% CI = 1.55-5.17), but not MVPAsr. These ORs remained significant after adjusting for all potential confounders except body mass index, after which only MVPAsr in women and MVPAb in men remained significant.

CONCLUSION

Individuals who do not meet the PA guidelines exhibited greater odds of having metabolic syndrome. This relationship tended to be stronger for objective PA measures than for self-report.

Does increasing steps per day predict improvement in physical function and pain interference in adults with fibromyalgia?

OBJECTIVE

To examine the concurrent and predictive associations between the number of steps taken per day and clinical outcomes in patients with fibromyalgia (FM).

METHODS

A total of 199 adults with FM (mean age 46.1 years, 95% women) who were enrolled in a randomized clinical trial wore a hip-mounted accelerometer for 1 week and completed self-report measures of physical function (Fibromyalgia Impact Questionnaire-Physical Impairment [FIQ-PI], Short Form 36 [SF-36] health survey physical component score [PCS], pain intensity and interference (Brief Pain Inventory [BPI]), and depressive symptoms (Patient Health Questionnaire-8 [PHQ-8]) as part of their baseline and followup assessments. Associations of steps per day with self-report clinical measures were evaluated from baseline to week 12 using multivariate regression models adjusted for demographic and baseline covariates.

RESULTS

Study participants were primarily sedentary, averaging 4,019 ± 1,530 steps per day. Our findings demonstrate a linear relationship between the change in steps per day and improvement in health outcomes for FM. Incremental increases on the order of 1,000 steps per day were significantly associated with (and predictive of) improvements in FIQ-PI, SF-36 PCS, BPI pain interference, and PHQ-8 (all P < 0.05). Although higher step counts were associated with lower FIQ and BPI pain intensity scores, these were not statistically significant.

CONCLUSION

Step count is an easily obtained and understood objective measure of daily physical activity. An exercise prescription that includes recommendations to gradually accumulate at least 5,000 additional steps per day may result in clinically significant improvements in outcomes relevant to patients with FM. Future studies are needed to elucidate the dose-response relationship between steps per day and patient outcomes in FM.

Low-intensity daily walking activity is associated with hippocampal volume in older adults

Hippocampal atrophy is associated with memory impairment and dementia and serves as a key biomarker in the preclinical stages of Alzheimer's disease. Physical activity, one of the most promising behavioral interventions to prevent or delay cognitive decline, has been shown to be associated with hippocampal volume; specifically increased aerobic activity and fitness may have a positive effect on the size of the hippocampus. The majority of older adults, however, are sedentary and have difficulty initiating and maintaining exercise programs. A modestly more active lifestyle may nonetheless be beneficial. This study explored whether greater objectively measured daily walking activity was associated with larger hippocampal volume. We additionally explored whether greater low-intensity walking activity, which may be related to leisure-time physical, functional, and social activities, was associated with larger hippocampal volume independent of exercise and higher-intensity walking activity. Segmentation of hippocampal volumes was performed using Functional Magnetic Resonance Imaging of the Brain's Software Library (FSL), and daily walking activity was assessed using a step activity monitor on 92, nondemented, older adult participants. After controlling for age, education, body mass index, cardiovascular disease risk factors, and the Mini Mental State Exam, we found that a greater amount, duration, and frequency of total daily walking activity were each associated with larger hippocampal volume among older women, but not among men. These relationships were specific to hippocampal volume, compared with the thalamus, used as a control brain region, and remained significant for low-intensity walking activity, independent of moderate- to vigorous-intensity activity and self-reported exercise. This is the first study, to our knowledge, to explore the relationship between objectively measured daily walking activity and hippocampal volume in an older adult population. Findings suggest the importance of examining whether increasing nonexercise, lifestyle physical activities may produce measurable cognitive benefits and affect hippocampal volume through molecular pathways unique to those related to moderate-intensity exercise.

The relationship between physical activity and metabolic syndrome in people with chronic obstructive pulmonary disease

BACKGROUND

The prevalence of metabolic syndrome has been reported to be 20% to 50% in people with chronic obstructive pulmonary disease (COPD). Because such people are sedentary and physically inactive, they are at risk of metabolic syndrome. The extent of this problem, however, is not fully understood.

OBJECTIVES

This study examined the relationship of sedentary time and physical activity to metabolic syndrome and the components of metabolic syndrome in a population-based sample of people with COPD.

METHODS

This was a secondary analysis of existing cross-sectional data. Subjects with COPD (n = 223) were drawn from the National Health and Nutrition Examination Survey data set (2003-2006). Physical activity was measured by accelerometry. Waist circumference, triglyceride level, high-density lipoprotein cholesterol level, blood pressure, and fasting glucose level were used to describe metabolic syndrome. Descriptive and inferential statistics were used for analysis.

RESULTS

Fifty-five percent of the sample had metabolic syndrome. No significant differences in sedentary time and level of physical activity were found in people with COPD and metabolic syndrome and people with COPD only. However, those with a mean activity count of greater than 240 counts per minute had a lower prevalence of metabolic syndrome. Waist circumference and glucose level were significantly associated with the time spent in sedentary, light, and moderate to vigorous physical activity.

CONCLUSION

Metabolic syndrome is highly prevalent in people with COPD, and greater physical activity and less sedentary time are associated with lower rates of metabolic syndrome. This suggests that interventions to decrease the risk of metabolic syndrome in people with COPD should include both reducing sedentary time and increasing the time and intensity of physical activity.

Validity of the Bite Counter device in a controlled laboratory setting

Body-borne sensors may be useful in assessing eating behaviors and have the potential to overcome some of the limitations of self-report instruments. The Bite Counter is a new commercial device, worn on the wrist that purports to track the number of bites taken per day. It contains a tri-axial accelerometer that detects an upward, arcing motion from the table to the mouth, known as a wrist roll.

PURPOSE

To examine the validity of the Bite Counter device for measuring bites in individuals while consuming various foods and beverages.

METHODS

15 adults (23-58 years old) wore the device on the wrist of their dominant hand. They were presented with a meal consisting of foods/beverages, each consumed with different utensils: meat (knife and fork), side items (fork), soup (spoon), pizza (hands), can of soda (hands), and a smoothie (straw). Each food or drink was consumed by itself, in consecutive order. A researcher observed them through a one-way mirror and counted the number of bites taken.

RESULTS

The percentage of actual bites taken varied as follows: Meat (127%), side items (82.6%), soup (60.2%), pizza (87.3%), soda (81.7%), and smoothie (57.7%). The overall mean was 81.2% of bites taken.

CONCLUSION

The results indicate that the Bite Counter holds promise for being able to count the number of hand-to-mouth movements. In general, it underestimated hand-to-mouth movements, but some types of hand movements caused overestimation of bites. Future studies should be undertaken to improve the sensitivity and specificity of the Bite Counter device.

The effect of pedometer use on physical activity and body weight in obese women

Physical activity and healthy eating are of the utmost importance in treatment of obesity. However obese generally tend to have a sedentary lifestyle. Walking is a form of physical activity that is both simple and can be performed by everyone, but it requires an objective measurement. Number of steps taken during tracking can be recorded with the pedometer, a device used to measure the level of physical activity. We aimed to investigate whether or not using pedometers as a motivational technique to increase the level of physical activity in obese women has an impact on weight loss. Eighty-four obese women who are similar age referring to Ataturk University Faculty of Medicine Healthy Living Clinic, Turkey were randomly divided into two groups. Intervention group were given pedometers, and control group were prescribed similar diet and physical activity with a three-month follow-up plan without pedometers. Mean weight in pedometer group initially was 88.9 ± 8.4 kg, which decreased to 80.2 ± 8.7 kg after the programme. Mean weight in control group was 86.1 ± 9.2 kg at the beginning, and it decreased to 84.7 ± 8.8 kg after three months. It was observed in pedometer group that the mean number of steps 8817 ± 2725 steps/day at the beginning increased to mean 9716 ± 2811 steps/day at the end of the study. Weight, body mass index, body fat percentage and waist circumference measurements decreased more greatly in the pedometer when compared to the control group (p < 0.001). Pedometers may be recommended to obese patients to monitor and increase the level of physical activity and to promote weight loss.

Physiological and perceptual responses to Latin partnered social dance

The purpose of this study was to investigate the physiological and perceptual responses to Latin partnered social dance to salsa music when performed as a self-selected activity within an ecologically valid setting. Eighteen non-professional adult Latin dancers undertook a laboratory-based graded exercise test for determination of maximal oxygen uptake and maximal heart rate. The dancers then attended two Latin partnered social dance sessions in established salsa venues in London, UK over a 2 wk period. Physiological data were collected using a wrist-worn ActiGraph wGT3X+ accelerometer with accompanying heart rate monitor. Perceived benefits of dance were assessed via the Exercise Benefits/Barriers Scale, and measurement of state intrinsic motivation during dance was undertaken using the Intrinsic Motivation Inventory. Total step count during 2h of dance was not different (t16 = -.39, p = .71) between females and males (9643 ± 1735 step); however, women expended a significantly lower (t16 = -2.57, p < .05) total energy expenditure when compared to men (479 ± 125 versus 651 ± 159 kcal). Dancers of both genders considered interest-enjoyment to be the motivator of primary importance. The highest rated perceived benefit of dance was psychological outlook. Latin partnered social dance to salsa music demands moderate to vigorous physical activity intensity levels, and further, fosters interest, enjoyment, and a positive psychological outlook among novice to advanced adult Latin dancers taking part primarily for leisure purposes. These findings may be of use for those interested in the efficacy of Latin social dancing as an expressive medium for the promotion of community health.

Estimating activity and sedentary behavior from an accelerometer on the hip or wrist

PURPOSE

Previously, the National Health and Examination Survey measured physical activity with an accelerometer worn on the hip for 7 d but recently changed the location of the monitor to the wrist. This study compared estimates of physical activity intensity and type with an accelerometer on the hip versus the wrist.

METHODS

Healthy adults (n = 37) wore triaxial accelerometers (Wockets) on the hip and dominant wrist along with a portable metabolic unit to measure energy expenditure during 20 activities. Motion summary counts were created, and receiver operating characteristic (ROC) curves were then used to determine sedentary and activity intensity thresholds. Ambulatory activities were separated from other activities using the coefficient of variation of the counts. Mixed-model predictions were used to estimate activity intensity.

RESULTS

The ROC for determining sedentary behavior had greater sensitivity and specificity (71% and 96%) at the hip than at the wrist (53% and 76%), as did the ROC for moderate- to vigorous-intensity physical activity on the hip (70% and 83%) versus the wrist (30% and 69%). The ROC for the coefficient of variation associated with ambulation had a larger AUC at the hip compared to the wrist (0.83 and 0.74). The prediction model for activity energy expenditure resulted in an average difference of 0.55 ± 0.55 METs on the hip and 0.82 ± 0.93 METs on the wrist.

CONCLUSIONS

Methods frequently used for estimating activity energy expenditure and identifying activity intensity thresholds from an accelerometer on the hip generally do better than similar data from an accelerometer on the wrist. Accurately identifying sedentary behavior from a lack of wrist motion presents significant challenges.

Association between habitual physical activity and lower cardiovascular risk in premenopausal, perimenopausal, and postmenopausal women: a population-based study

OBJECTIVE

Menopause is associated with an increased risk of cardiovascular disease. Habitual physical activity, defined as any form of body movement with energy expenditure above resting levels, may improve health parameters. We assessed the level of habitual physical activity and its effect on anthropometric measures and cardiovascular risk factors in a cohort of premenopausal, perimenopausal, and postmenopausal women.

METHODS

This cross-sectional study is nested on a longitudinal population-based study that was begun in 1995 in the city of Passo Fundo, Brazil. For the present analysis, 292 women were included. Anthropometric and metabolic profile was evaluated. Habitual physical activity was assessed by a digital pedometer for 7 days, and participants were stratified into active and inactive (≥6,000 and <6,000 steps/day, respectively).

RESULTS

The mean (SD) age was 57.1 (5.4) years. The average number of steps per day for the total sample was 5,250.7 (3,372.9): 3,472.4 (1,570.2) in the inactive group (61.8%) and 9,055.9 (3,033.4) in the active group (31.9%). A negative and statistically significant correlation was found between physical activity and smoking (P = -0.019), body mass index (P = -0.006), waist circumference (P = -0.013), and waist-to-hip ratio of 0.85 or higher (P = -0.043). Inactive women presented a higher risk of overweight/obesity (odds ratio [OR], 2.1; 95% CI, 1.233-3.622; P = 0.006) and waist circumference larger than 88 cm (OR, 1.7; 95% CI, 1.054-2.942; P = 0.03), even after adjustment for age, menopause status, smoking, and hormone therapy. Inactive women also had a higher risk of diabetes mellitus (OR, 2.7; 95% CI, 1.233-6.295; P = 0.014) and metabolic syndrome (OR, 2.5, 95% CI, 1.443-4.294; P = 0.001).

CONCLUSIONS

Habitual physical activity, specifically walking 6,000 or more steps daily, was associated with a decreased risk of cardiovascular disease and diabetes in middle-aged women, independently of menopause status.