b s t r a c tStress-related eating may be a potential factor in the obesity epidemic. Rather little is known about how stress associates with eating behavior and food intake in overweight individuals in a free-living situation. Thus, the present study aims to investigate this question in psychologically distressed overweight and obese working-aged Finns. The study is a cross-sectional baseline analysis of a randomized controlled trial. Of the 339 study participants, those with all the needed data available (n ¼ 297, 84% females) were included. The mean age was 48.9 y (SD ¼ 7.6) and mean body mass index 31.3 kg/m 2 (SD ¼ 3.0). Perceived stress and eating behavior were assessed by self-reported questionnaires Perceived Stress Scale (PSS), Intuitive Eating Scale, the Three-Factor Eating Questionnaire, Health and Taste Attitude Scales and ecSatter Inventory. Diet and alcohol consumption were assessed by 48-h dietary recall, Index of Diet Quality, and AUDIT-C. Individuals reporting most perceived stress (i.e. in the highest PSS tertile) had less intuitive eating, more uncontrolled eating, and more emotional eating compared to those reporting less perceived stress (p < 0.05). Moreover, individuals in the highest PSS tertile reported less cognitive restraint and less eating competence than those in the lowest tertile (p < 0.05). Intake of whole grain products was the lowest among those in the highest PSS tertile (p < 0.05). Otherwise the quality of diet and alcohol consumption did not differ among the PSS tertiles.In conclusion, high perceived stress was associated with the features of eating behavior that could in turn contribute to difficulties in weight management. Stress-related way of eating could thus form a potential risk factor for obesity. More research is needed to develop efficient methods for clinicians to assist in handling stress-related eating in the treatment of obese people.

BackgroundThe present study aimed to investigate how subjective self-reported stress is associated with objective heart rate variability (HRV)-based stress and recovery on workdays. Another aim was to investigate how physical activity (PA), body composition, and age are associated with subjective stress, objective stress, and recovery.MethodsWorking-age participants (n = 221; 185 women, 36 men) in this cross-sectional study were overweight (body mass index, 25.3–40.1 kg/m2) and psychologically distressed (≥3/12 points on the General Health Questionnaire). Objective stress and recovery were based on HRV recordings over 1–3 workdays. Subjective stress was assessed by the Perceived Stress Scale. PA level was determined by questionnaire, and body fat percentage was assessed by bioelectrical impedance analysis.ResultsSubjective stress was directly associated with objective stress (P = 0.047) and inversely with objective recovery (P = 0.046). These associations persisted after adjustments for sex, age, PA, and body fat percentage. Higher PA was associated with lower subjective stress (P = 0.037). Older age was associated with higher objective stress (P < 0.001). After further adjustment for alcohol consumption and regular medication, older age was associated with lower subjective stress (P = 0.043).ConclusionsThe present results suggest that subjective self-reported stress is associated with objective physiological stress, but they are also apparently affected by different factors. However, some of the found associations among these overweight and psychologically distressed participants with low inter-individual variation in PA are rather weak and the clinical value of the present findings should be studied further among participants with greater heterogeneity of stress, PA and body composition. However, these findings suggest that objective stress assessment provides an additional aspect to stress evaluation. Furthermore, the results provide valuable information for developing stress assessment methods.

BackgroundPhysical 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.MethodsThe 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/m2). 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.ResultsHigh 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).ConclusionIndependent 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3391-4) contains supplementary material, which is available to authorized users.

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.

The aim of this study was to investigate the association between physical activity (PA) and objective heart rate variability (HRV)-based stress and recovery with subjective stress in a longitudinal setting. Working-age participants (n = 221; 185 women, 36 men) were overweight (body mass index, 25.3-40.1 kg/m ) and psychologically distressed (≥3/12 points on the General Health Questionnaire). Objective stress and recovery were based on HRV recordings over 1-3 work days. Subjective stress was assessed with the Perceived Stress Scale and PA level with a questionnaire. Data were collected at three time points: baseline, 10 weeks post intervention, and at the 36-week follow-up. We adopted a latent growth model to investigate the initial level and change in PA, objective stress and recovery, and subjective stress at the three measurement time points. The results showed that initial levels of PA (P < 0.001) and objective stress (P = 0.001) and recovery (P < 0.01) were associated with the change in subjective stress. The results persisted after adjustment for intervention group. The present results suggest that high PA and objectively assessed low stress and good recovery have positive effects on changes in subjective stress in the long-term.

A strong sense of meaningfulness and better recovery from stress predict an increase in PA among physically inactive and overweight young adults. Therefore, participants with a low sense of meaningfulness and low recovery from stress may require support from other interventions to be able to increase their PA.

Background Epigenetic clocks are based on DNA methylation (DNAm). It has been suggested that these clocks are useable markers of biological aging and premature mortality. Because genetic factors explain variations in both epigenetic aging and mortality, this association could also be explained by shared genetic factors. We investigated the influence of genetic and lifestyle factors (smoking, alcohol consumption, physical activity, chronic diseases, body mass index) and education on the association of accelerated epigenetic aging with mortality using a longitudinal twin design. Utilizing a publicly available online tool, we calculated the epigenetic age using two epigenetic clocks, Horvath DNAmAge and DNAm GrimAge, in 413 Finnish twin sisters, aged 63–76 years, at the beginning of the 18-year mortality follow-up. Epigenetic age acceleration was calculated as the residuals from a linear regression model of epigenetic age estimated on chronological age (AAHorvath, AAGrimAge, respectively). Cox proportional hazard models were conducted for individuals and twin pairs. Results The results of the individual-based analyses showed an increased mortality hazard ratio (HR) of 1.31 (CI95: 1.13–1.53) per one standard deviation (SD) increase in AAGrimAge. The results indicated no significant associations of AAHorvath with mortality. Pairwise mortality analyses showed an HR of 1.50 (CI95: 1.02–2.20) per 1 SD increase in AAGrimAge. However, after adjusting for smoking, the HR attenuated substantially and was statistically non-significant (1.29; CI95: 0.84–1.99). Similarly, in multivariable adjusted models the HR (1.42–1.49) was non-significant. In AAHorvath, the non-significant HRs were lower among monozygotic pairs in comparison to dizygotic pairs, while in AAGrimAge there were no systematic differences by zygosity. Further, the pairwise analysis in quartiles showed that the increased within pair difference in AAGrimAge was associated with a higher all-cause mortality risk. Conclusions In conclusion, the findings suggest that DNAm GrimAge is a strong predictor of mortality independent of genetic influences. Smoking, which is known to alter DNAm levels and is built into the DNAm GrimAge algorithm, attenuated the association between epigenetic aging and mortality risk.

Background Measures of biological aging range from DNA methylation (DNAm)-based estimates to measures of physical abilities. The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. Methods We studied 63- to 76-year-old women (N = 395) from the Finnish Twin Study on Aging (FITSA). Participants’ biological age (epigenetic clocks DNAm GrimAge and DunedinPACE) was estimated using blood DNAm data. Tests of physical functioning conducted under standardized laboratory conditions included the Timed Up and Go (TUG) test and 10-m walk test. Mortality hazard ratios (HRs) were calculated per every one standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. Results During the follow-up period (mean 17.0 years, range 0.2–20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. Conclusions The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each other’s and genetic influences. DNAm-based measures and functional tests capture different aspects of the aging process and thus complement each other as measures of biological aging in predicting mortality.