Effect of short-term weight loss on mental stress-induced cardiovascular and pro-inflammatory responses in women

Epidemiologic evidence links psychosocial stress with obesity but experimental studies examining the mechanisms that mediates the effect of stress on adiposity are scarce. The aim of this study was to investigate whether changes in adiposity following minimal weight loss affect heightened stress responses in women, and examine the role of the adipokine leptin in driving inflammatory responses. Twenty-three overweight or obese, but otherwise healthy, women (M age ¼ 30.41 ± 8.0 years; BMI ¼ 31.9 ± 4.1 kg/m2 ) completed standardized acute mental stress before and after a 9-week calorie restriction program designed to modify adiposity levels. Cardiovascular (blood pressure and heart rate) and inflammatory cytokines (leptin and interleukin-6; IL-6) responses to mental stress were assessed several times between baseline and a 45-min post-stress recovery period. There were modest changes in adiposity measures while the adipokine leptin was markedly reduced (27%) after the intervention. Blood pressure reactivity was attenuated (3.38 ± 1.39 mmHg) and heart rate recovery was improved (2.07 ± 0.96 Bpm) after weight loss. Blood pressure responses were inversely associated with changes in waist to hip ratio post intervention. Decreased levels of circulating leptin following weight loss were inversely associated with the IL-6 inflammatory response to stress (r ¼ 0.47). We offered preliminary evidence suggesting that modest changes in adiposity following a brief caloric restriction program may yield beneficial effect on cardiovascular stress responses. In addition, reductions in basal leptin activity might be important in blunting pro-inflammatory responses. Large randomized trials of the effect of adiposity on autonomic responses are thus warranted

Weekday and weekend patterns of objectively measured sitting, standing, and stepping in a sample of office-based workers: the active buildings study

Background: There is a growing body of research into the total amount and patterns of sitting, standing and stepping in office-based workers and few studies using objectively measured sitting and standing. Understanding these patterns may identify daily times opportune for interventions to displace sitting with activity. Methods: A sample of office-based workers (n = 164) residing in England were fitted with thigh-worn ActivPal accelerometers and devices were worn 24 hours a day for five consecutive days, always including Saturday and Sunday and during bathing and sleeping. Daily amounts and patterns of time spent sitting, standing, stepping and step counts and frequency of sit/stand transitions, recorded by the ActivPal accelerometer, were reported. Results: Total sitting/standing time was similar on weekdays (10.6/4.1 hrs) and weekends (10.6/4.3 hrs). Total step count was also similar over weekdays (9682 ± 3872) and weekends (9518 ± 4615). The highest physical activity levels during weekdays were accrued at 0700 to 0900, 1200 to 1400, and 1700 to 1900; and during the weekend at 1000 to 1700. During the weekday the greatest amount of sitting was accrued at 0900 to 1200, 1400 to 1700, and 2000 to 2300, and on the weekend between 1800 and 2300. During the weekday the greatest amount of standing was accrued between 0700 and 1000 and 1700 and 2100, and on the weekend between 1000 and 1800. On the weekday the highest number of sit/stand transitions occurred between 0800 to 0900 and remained consistently high until 1800. On the weekend, the highest number occurred between 1000 to 1400 and 1900 to 2000. Conclusion: Office based-workers demonstrate high levels of sitting during both the working week and weekend. Interventions that target the working day and the evenings (weekday and weekend) to displace sitting with activity may offer most promise for reducing population levels of sedentary behaviour and increasing physical activity levels, in office-based workers residing in England

Active buildings: modelling physical activity and movement in office buildings. An observational study protocol

Introduction: Health benefits of regular participation in physical activity are well documented but population levels are low. Office layout, and in particular the number and location of office building destinations (eg, print and meeting rooms), may influence both walking time and characteristics of sitting time. No research to date has focused on the role that the layout of the indoor office environment plays in facilitating or inhibiting step counts and characteristics of sitting time. The primary aim of this study was to investigate associations between office layout and physical activity, as well as sitting time using objective measures. Methods and analysis Active buildings is a unique collaboration between public health, built environment and computer science researchers. The study involves objective monitoring complemented by a larger questionnaire arm. UK office buildings will be selected based on a variety of features, including office floor area and number of occupants. Questionnaires will include items on standard demographics, well-being, physical activity behaviour and putative socioecological correlates of workplace physical activity. Based on survey responses, approximately 30 participants will be recruited from each building into the objective monitoring arm. Participants will wear accelerometers (to monitor physical activity and sitting inside and outside the office) and a novel tracking device will be placed in the office (to record participant location) for five consecutive days. Data will be analysed using regression analyses, as well as novel agent-based modelling techniques. Ethics and dissemination The results of this study will be disseminated through peer-reviewed publications and scientific presentations. Ethical approval was obtained through the University College London Research Ethics Committee (Reference number 4400/001)

Happiness ratings adjusted for age, gender, and wealth.

<p>Mean happiness ratings (95% CI) adjusted for age, gender and wealth for respondents with no chronic condition and for all eight conditions. Higher scores indicate greater happiness.</p

Quality of life scores adjusted for age, gender, and wealth.

<p>Mean quality of life scores (95% CI) as measured by the CASP-19, adjusted for age, gender and wealth for respondents with no chronic condition and for all eight chronic conditions. Higher scores indicate better QOL.</p

Percentage depressed mood adjusted for age, gender, and wealth.

<p>Percentage of depressed mood (95% CI), adjusted for age, gender and wealth, for respondents with no condition and for all eight chronic conditions. Higher scores indicate greater depressed mood.</p

Quality of life and affective well-being for each illness compared with having no chronic illness.

<p>*Adjusted for age, gender and wealth. All values at p<0.005.</p

Participant characteristics.

<p>Mean (Standard deviation [SD]) and N (%).</p>1<p>Quality of life assessed using CASP-19. Scores could range from 0 to 57.</p>2<p>Happiness assessed using two items drawn from the GHQ-12, namely ‘Have you recently been able to enjoy your normal day-to-day activities?’ and ‘Have you recently been feeling reasonably happy, all things considered?’. Scores could range from 0 to 6.</p>3<p>Depression was assessed using the CES-D. Scores could range from 0 to 8. Total scores = >4 indicate presence of depressed mood (yes), scores = <3 indicate absence of depressed mood (no).</p><p>SES = Socioeconomic status.</p

Co-morbidity and quality of life (a), happiness (b) and depressed mood (c).

<p>Panel (a) shows the mean quality of life scores (95% CI) for respondents with one, two, three and four or more conditions compared with those without a chronic condition, adjusted for age, gender and wealth. Higher scores indicate better QOL. Panel (b) shows the mean happiness ratings (95% CI) for respondents with no condition compared with one, two, three and four or more co-morbid chronic conditions, adjusted for age, gender and wealth. Higher scores indicate greater happiness. Panel (c) show the percentage of depressed mood, adjusted for age, gender and wealth, for respondents with one, two, three and four or more co-morbid conditions compared with those respondents with no chronic condition.</p

Additional file 2: of Development and validation of the Self-Regulation of Eating Behaviour Questionnaire for adults

Scree plot and Parallel analyses of the final 5 items retained in the ‘Internal Reliability and Factor Structure Study’. (DOCX 38 kb