Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users.

BACKGROUND: Frequent self-weighing is associated with successful weight loss and weight maintenance during and after weight loss interventions. Less is known about self-weighing behaviors and associated weight change in free-living settings. OBJECTIVE: This study aimed to investigate the association between the frequency of self-weighing and changes in body weight in a large international cohort of smart scale users. METHODS: This was an observational cohort study with 10,000 randomly selected smart scale users who had used the scale for at least 1 year. Longitudinal weight measurement data were analyzed. The association between the frequency of self-weighing and weight change over the follow-up was investigated among normal weight, overweight, and obese users using Pearson's correlation coefficient and linear models. The association between the frequency of self-weighing and temporal weight change was analyzed using linear mixed effects models. RESULTS: The eligible sample consisted of 9768 participants (6515/9768, 66.7% men; mean age 41.5 years; mean BMI 26.8 kg/m2). Of the participants, 4003 (4003/9768, 41.0%), 3748 (3748/9768, 38.4%), and 2017 (2017/9768, 20.6%) were normal weight, overweight, and obese, respectively. During the mean follow-up time of 1085 days, the mean weight change was -0.59 kg, and the mean percentage of days with a self-weigh was 39.98%, which equals 2.8 self-weighs per week. The percentage of self-weighing days correlated inversely with weight change, r=-0.111 (P<.001). Among normal weight, overweight, and obese individuals, the correlations were r=-0.100 (P<.001), r=-0.125 (P<.001), and r=-0.148 (P<.001), respectively. Of all participants, 72.5% (7085/9768) had at least one period of ≥30 days without weight measurements. During the break, weight increased, and weight gains were more pronounced among overweight and obese individuals: 0.58 kg in the normal weight group, 0.93 kg in the overweight group, and 1.37 kg in the obese group (P<.001). CONCLUSIONS: Frequent self-weighing was associated with favorable weight loss outcomes also in an uncontrolled, free-living setting, regardless of specific weight loss interventions. The beneficial associations of regular self-weighing were more pronounced for overweight or obese individuals.

Prediction of Self-Perceived Stress and Arousal Based on Electrodermal Activity.

Electrodermal activity (EDA) reflects the functions of autonomic nervous system and is often used in evaluation of mental states, e.g. short- and long-term stress. In this study, test subjects were exposed to a 3-phase adapted MIST test (relaxation, arousal, stress) during which EDA was recorded, and the self-perceived stress and arousal were assessed. The objective of the study was to evaluate the feasibility of EDA features to predict the MIST test phases and self-perceived stress and arousal. With EDA features, the test phases were classified with accuracy of 94.1%, and the self-perceived stress and arousal were classified with accuracy of 60.5-72.2%. Results are promising for the use of EDA for long-term assessment of self-perceived stress and arousal during work.

Activity Level and Body Mass Index as Predictors of Physical Workload During Working Career.

The increasing prevalence of inactivity and obesity, along with aging, has implications on work capacity of labor force. This study reports the relationships between activity level and BMI by age with objectively measured physical workload. Data were examined from a sample of 19 481 Finnish employees using an estimate of minute-to-minute oxygen consumption based on R-R interval recordings. The mean estimated %VO2max during the working day was 12.1 (±3.6) and 15.1 (±4.5)% for men and women, respectively. Based on a linear model, the mean %VO2max increased by 1.5%-unit per 10-year increase in age, by 2.1%-unit per 5 kg/m2 increase in BMI, and decreased by 1.6%-unit if improving physical activity class by two (p < 0.001 for all). Overweight and obesity, together with inactivity, notably increases workload throughout the career, even though at young adulthood, the daily workload is almost the same for each person regardless of the BMI, activity level, or gender. This study highlights the importance of regular physical activity and normal weight in protecting the worker from excessive physical (cardiovascular) workload during the whole working career.

Acute Effect of Alcohol Intake on Cardiovascular Autonomic Regulation During the First Hours of Sleep in a Large Real-World Sample of Finnish Employees: Observational Study.

BACKGROUND: Sleep is fundamental for good health, and poor sleep has been associated with negative health outcomes. Alcohol consumption is a universal health behavior associated with poor sleep. In controlled laboratory studies, alcohol intake has been shown to alter physiology and disturb sleep homeostasis and architecture. The association between acute alcohol intake and physiological changes has not yet been studied in noncontrolled real-world settings. OBJECTIVE: The aim of this study was to assess the effects of alcohol intake on the autonomic nervous system (ANS) during sleep in a large noncontrolled sample of Finnish employees. METHODS: From a larger cohort, this study included 4098 subjects (55.81%, 2287/4098 females; mean age 45.1 years) who had continuous beat-to-beat R-R interval recordings of good quality for at least 1 day with and for at least 1 day without alcohol intake. The participants underwent continuous beat-to-beat R-R interval recording during their normal everyday life and self-reported their alcohol intake as doses for each day. Heart rate (HR), HR variability (HRV), and HRV-derived indices of physiological state from the first 3 hours of sleep were used as outcomes. Within-subject analyses were conducted in a repeated measures manner by studying the differences in the outcomes between each participant's days with and without alcohol intake. For repeated measures two-way analysis of variance, the participants were divided into three groups: low (≤0.25 g/kg), moderate (>0.25-0.75 g/kg), and high (>0.75 g/kg) intake of pure alcohol. Moreover, linear models studied the differences in outcomes with respect to the amount of alcohol intake and the participant's background parameters (age; gender; body mass index, BMI; physical activity, PA; and baseline sleep HR). RESULTS: Alcohol intake was dose-dependently associated with increased sympathetic regulation, decreased parasympathetic regulation, and insufficient recovery. In addition to moderate and high alcohol doses, the intraindividual effects of alcohol intake on the ANS regulation were observed also with low alcohol intake (all P<.001). For example, HRV-derived physiological recovery state decreased on average by 9.3, 24.0, and 39.2 percentage units with low, moderate, and high alcohol intake, respectively. The effects of alcohol in suppressing recovery were similar for both genders and for physically active and sedentary subjects but stronger among young than older subjects and for participants with lower baseline sleep HR than with higher baseline sleep HR. CONCLUSIONS: Alcohol intake disturbs cardiovascular relaxation during sleep in a dose-dependent manner in both genders. Regular PA or young age do not protect from these effects of alcohol. In health promotion, wearable HR monitoring and HRV-based analysis of recovery might be used to demonstrate the effects of alcohol on sleep on an individual level.

An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial AccelerometerWrist-Band.

Wrist-worn sensors have better compliance for activity monitoring compared to hip, waist, ankle or chest positions. However, wrist-worn activity monitoring is challenging due to the wide degree of freedom for the hand movements, as well as similarity of hand movements in different activities such as varying intensities of cycling. To strengthen the ability of wrist-worn sensors in detecting human activities more accurately, motion signals can be complemented by physiological signals such as optical heart rate (HR) based on photoplethysmography. In this paper, an activity monitoring framework using an optical HR sensor and a triaxial wrist-worn accelerometer is presented. We investigated a range of daily life activities including sitting, standing, household activities and stationary cycling with two intensities. A random forest (RF) classifier was exploited to detect these activities based on the wrist motions and optical HR. The highest overall accuracy of 89.6 ± 3.9% was achieved with a forest of a size of 64 trees and 13-s signal segments with 90% overlap. Removing the HR-derived features decreased the classification accuracy of high-intensity cycling by almost 7%, but did not affect the classification accuracies of other activities. A feature reduction utilizing the feature importance scores of RF was also carried out and resulted in a shrunken feature set of only 21 features. The overall accuracy of the classification utilizing the shrunken feature set was 89.4 ± 4.2%, which is almost equivalent to the above-mentioned peak overall accuracy.

Physical Activity: Absolute Intensity versus Relative-to-Fitness-Level Volumes.

PURPOSE: This study aimed to investigate in a real-life setting how moderate- and vigorous-intensity physical activity (PA) volumes differ according to absolute intensity recommendation and relative to individual fitness level by sex, age, and body mass index. METHODS: A total of 23,224 Finnish employees (10,201 men and 13,023 women; ages 18-65 yr; body mass index = 18.5-40.0 kg·m) participated in heart rate recording for 2+ d. We used heart rate and its variability, respiration rate, and on/off response information from R-R interval data calibrated by participant characteristics to objectively determine daily PA volume, as follows: daily minutes of absolute moderate (3-<6 METs) and vigorous (≥6 METs) PA and minutes relative to individual aerobic fitness for moderate (40%-<60% of oxygen uptake reserve) and vigorous (≥60%) PA. RESULTS: According to absolute intensity categorization, the volume of both moderate- and vigorous-intensity PA was higher in men compared with women (P < 0.001), in younger compared with older participants (P < 0.001), and in normal weight compared with overweight or obese participants (P < 0.001). When the volume of PA intensity was estimated relative to individual fitness level, the differences were much smaller. Mean daily minutes of absolute vigorous-intensity PA were higher than those of relative intensity minutes in normal weight men ages 18-40 yr (17.7, 95% confidence interval [CI] = 16.9-18.6, vs 8.6, 95% CI = 8.0-9.1; P < 0.001), but the reverse was the case for obese women ages 41-65 yr (0.3, 95% CI = 0.2-0.4, vs 7.8, 95% CI = 7.2-8.4; P < 0.001). CONCLUSION: Compared with low-fit persons, high-fit persons more frequently reach an absolute target PA intensity, but reaching the target is more similar for relative intensity.

Physical activity, body mass index and heart rate variability-based stress and recovery in 16 275 Finnish employees: a cross-sectional study.

BACKGROUND: Physical inactivity, overweight, and work-related stress are major concerns today. Psychological stress causes physiological responses such as reduced heart rate variability (HRV), owing to attenuated parasympathetic and/or increased sympathetic activity in cardiac autonomic control. This study's purpose was to investigate the relationships between physical activity (PA), body mass index (BMI), and HRV-based stress and recovery on workdays, among Finnish employees. METHODS: The participants in this cross-sectional study were 16 275 individuals (6863 men and 9412 women; age 18-65 years; BMI 18.5-40.0 kg/m(2)). Assessments of stress, recovery and PA were based on HRV data from beat-to-beat R-R interval recording (mainly over 3 days). The validated HRV-derived variables took into account the dynamics and individuality of HRV. Stress percentage (the proportion of stress reactions, workday and working hours), and stress balance (ratio between recovery and stress reactions, sleep) describe the amount of physiological stress and recovery, respectively. Variables describing the intensity (i.e. magnitude of recognized reactions) of physiological stress and recovery were stress index (workday) and recovery index (sleep), respectively. Moderate to vigorous PA was measured and participants divided into the following groups, based on calculated weekly PA: inactive (0 min), low (0 < 150 min), medium (150-300 min), and high (>300 min). BMI was calculated from self-reported weight and height. Linear models were employed in the main analyses. RESULTS: High PA was associated with lower stress percentages (during workdays and working hours) and stress balance. Higher BMI was associated with higher stress index, and lower stress balance and recovery index. These results were similar for men and women (P < 0.001 for all). CONCLUSION: Independent of age and sex, high PA was associated with a lower amount of stress on workdays. Additionally, lower BMI was associated with better recovery during sleep, expressed by a greater amount and magnitude of recovery reactions, which suggests that PA in the long term resulting in improved fitness has a positive effect on recovery, even though high PA may disturb recovery during the following night. Obviously, several factors outside of the study could also affect HRV-based stress.

Exploratory analysis of associations between individual lifestyles and heart rate variability -based recovery during sleep.

Sleep is the most important period for recovering from daily stress and load. Assessment of the stress recovery during sleep is therefore, an important metric for care and quality of life. Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system (ANS) activity, and HRV-based methods can be used to assess physiological recovery, characterized by parasympathetic domination of the ANS. HRV is affected by multiple factors of which some are unmodifiable (such as age and gender) but many are related to daily lifestyle choices (e.g. alcohol consumption, physical activity, sleeping times). The purpose of this study was to investigate the association of these aforementioned factors on HRV-based recovery during sleep on a large sample. Variable importance measures yielded by random forest were used for identifying the most relevant predictors of sleep-time recovery. The results emphasize the disturbing effects of alcohol consumption on sleep-time recovery. Good physical fitness is associated to good recovery, but acute physical activity seems to challenge or delay the recovery process for the next night. Longer sleeping time enables more recovery minutes, but the proportion of recovery (i.e. recovery efficiency) seems to peak around 7.0-7.25 hours of sleep.

Objectively measured physical activity in Finnish employees: a cross-sectional study.

OBJECTIVES: To objectively measure the amount of intensity-specific physical activity by gender and age with respect to body mass index (BMI) during workdays and days off among Finnish employees. DESIGN: A cross-sectional study. SETTING: Primary care occupational healthcare units. PARTICIPANTS: A sample of 9554 Finnish employees (4221 men and 5333 women; age range 18-65 years; BMI range 18.5-40 kg/m(2)) who participated in health assessments related to occupational health promotion. MAIN OUTCOME MEASUREMENTS: The amount of moderate-to-vigorous (MVPA) and vigorous (VPA) physical activity (≥3 and ≥6 metabolic equivalents, respectively) was assessed by estimating the minute-to-minute oxygen consumption from the recorded beat-to-beat R-R interval data. The estimation method used heart rate, respiration rate and on/off response information from R-R interval data calibrated by age, gender, height, weight and self-reported physical activity class. The proportion of participants fulfilling the aerobic physical activity recommendation of ≥150 min/week was calculated on the basis of ≥10 min bouts, by multiplying the VPA minutes by 2. RESULTS: Both MVPA and VPA were higher among men and during days off, and decreased with increasing age and BMI (p<0.001 for all). Similar results were observed when the probability of having a bout of MVPA or VPA lasting continuously for ≥10 min per measurement day was studied. The total amount of VPA was low among overweight (mean ≤2.6 min/day), obese (mean ≤0.6 min/day) and all women in the age group 51-65 years (mean ≤2.5 min/day) during both types of days. The proportion of participants fulfilling the aerobic physical activity recommendation was highest for normal weight men (65%; 95% CI 62% to 67%) and lowest for obese women (10%; 95% CI 8% to 12%). CONCLUSIONS: Objectively measured physical activity is higher among men and during days off, and decreases with increasing age and BMI. The amount of VPA is very low among obese, overweight and older women.