Peter Murray

Validation of the Genea Accelerometer

PURPOSE The study aims were: 1) to assess the technical reliability and validity of the GENEA using a mechanical shaker; 2) to perform a GENEA value calibration to develop thresholds for sedentary and light-, moderate-, and vigorous-intensity physical activity; and 3) to compare the intensity classification of the GENEA with two widely used accelerometers. METHODS A total of 47 GENEA accelerometers were attached to a shaker and vertically accelerated, generating 15 conditions of varying acceleration and/or frequency. Reliability was calculated using SD and intrainstrument and interinstrument coefficients of variation, whereas validity was assessed using Pearson correlation with the shaker acceleration as the criterion. Next, 60 adults wore a GENEA on each wrist and on the waist (alongside an ActiGraph and RT3 accelerometer) while completing 10-12 activity tasks. A portable metabolic gas analyzer provided the criterion measure of physical activity. Analyses involved the use of Pearson correlations to establish criterion and concurrent validity and receiver operating characteristic curves to establish intensity cut points. RESULTS The GENEA demonstrated excellent technical reliability (CVintra = 1.4%, CVinter = 2.1%) and validity (r = 0.98, P < 0.001) using the mechanical shaker. The GENEA demonstrated excellent criterion validity using VO2 as the criterion (left wrist, r = 0.86; right wrist, r = 0.83; waist, r = 0.87), on par with the waist-worn ActiGraph and RT3. The GENEA demonstrated excellent concurrent validity compared with the ActiGraph (r = 0.92) and the RT3 (r = 0.97). The waist-worn GENEA had the greatest classification accuracy (area under the receiver operating characteristic curve (AUC) = 0.95), followed by the left (AUC = 0.93) and then the right wrist (AUC = 0.90). The accuracy of the waist-worn GENEA was virtually identical with that of the ActiGraph (AUC = 0.94) and RT3 (AUC = 0.95). CONCLUSION The GENEA is a reliable and valid measurement tool capable of classifying the intensity of physical activity in adults.

Physical Activity Classification Using the GENEA Wrist-Worn Accelerometer

INTRODUCTION Most accelerometer-based activity monitors are worn on the waist or lower back for assessment of habitual physical activity. Output is in arbitrary counts that can be classified by activity intensity according to published thresholds. The purpose of this study was to develop methods to classify physical activities into walking, running, household, or sedentary activities based on raw acceleration data from the GENEA (Gravity Estimator of Normal Everyday Activity) and compare classification accuracy from a wrist-worn GENEA with a waist-worn GENEA. METHODS Sixty participants (age = 49.4 ± 6.5 yr, body mass index = 24.6 ± 3.4 kg·m⁻²) completed an ordered series of 10-12 semistructured activities in the laboratory and outdoor environment. Throughout, three GENEA accelerometers were worn: one at the waist, one on the left wrist, and one on the right wrist. Acceleration data were collected at 80 Hz. Features obtained from both fast Fourier transform and wavelet decomposition were extracted, and machine learning algorithms were used to classify four types of daily activities including sedentary, household, walking, and running activities. RESULTS The computational results demonstrated that the algorithm we developed can accurately classify certain types of daily activities, with high overall classification accuracy for both waist-worn GENEA (0.99) and wrist-worn GENEA (right wrist = 0.97, left wrist = 0.96). CONCLUSIONS We have successfully developed algorithms suitable for use with wrist-worn accelerometers for detecting certain types of physical activities; the performance is comparable to waist-worn accelerometers for assessment of physical activity.

Why Some Women Look Young for Their Age

The desire of many to look young for their age has led to the establishment of a large cosmetics industry. However, the features of appearance that primarily determine how old women look for their age and whether genetic or environmental factors predominately influence such features are largely unknown. We studied the facial appearance of 102 pairs of female Danish twins aged 59 to 81 as well as 162 British females aged 45 to 75. Skin wrinkling, hair graying and lip height were significantly and independently associated with how old the women looked for their age. The appearance of facial sun-damage was also found to be significantly correlated to how old women look for their age and was primarily due to its commonality with the appearance of skin wrinkles. There was also considerable variation in the perceived age data that was unaccounted for. Composite facial images created from women who looked young or old for their age indicated that the structure of subcutaneous tissue was partly responsible. Heritability analyses of the appearance features revealed that perceived age, pigmented age spots, skin wrinkles and the appearance of sun-damage were influenced more or less equally by genetic and environmental factors. Hair graying, recession of hair from the forehead and lip height were influenced mainly by genetic factors whereas environmental factors influenced hair thinning. These findings indicate that women who look young for their age have large lips, avoid sun-exposure and possess genetic factors that protect against the development of gray hair and skin wrinkles. The findings also demonstrate that perceived age is a better biomarker of skin, hair and facial aging than chronological age.

Rates and Determinants of Uptake and Use of an Internet Physical Activity and Weight Management Program in Office and Manufacturing Work Sites in England: Cohort Study

Background Internet-based physical activity (PA) and weight management programs have the potential to improve employees’ health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health. Objective The aim of the study was to assess the use and nonuse (user attrition) of a Web-based and monitoring device–based PA and weight management program in a range of employees and to determine if engagement with the program was related to the employees’ baseline characteristics or measured outcomes. Methods Longitudinal observational study of a cohort of employees having access to the MiLife Web-based automated behavior change system. Employees were recruited from manufacturing and office sites in the North West and the South of England. Baseline health data were collected, and participants were given devices to monitor their weight and PA via data upload to the website. Website use, PA, and weight data were collected throughout the 12-week program. Results Overall, 12% of employees at the four sites (265/2302) agreed to participate in the program, with 130 men (49%) and 135 women (51%), and of these, 233 went on to start the program. During the program, the dropout rate was 5% (11/233). Of the remaining 222 Web program users, 173 (78%) were using the program at the end of the 12 weeks, with 69% (153/222) continuing after this period. Engagement with the program varied by site but was not significantly different between the office and factory sites. During the first 2 weeks, participants used the website, on average, 6 times per week, suggesting an initial learning period after which the frequency of website log-in was typically 2 visits per week and 7 minutes per visit. Employees who uploaded weight data had a significant reduction in weight (−2.6 kg, SD 3.2, P< .001). The reduction in weight was largest for employees using the program’s weight loss mode (−3.4 kg, SD 3.5). Mean PA level recorded throughout the program was 173 minutes (SE 12.8) of moderate/high intensity PA per week. Website interaction time was higher and attrition rates were lower (OR 1.38, P= .03) in those individuals with the greatest weight loss. Conclusions This Web-based PA and weight management program showed high levels of engagement across a wide range of employees, including overweight or obese workers, shift workers, and those who do not work with computers. Weight loss was observed at both office and manufacturing sites. The use of monitoring devices to capture and send data to the automated Web-based coaching program may have influenced the high levels of engagement observed in this study. When combined with objective monitoring devices for PA and weight, both use of the website and outcomes can be tracked, allowing the online coaching program to become more personalized to the individual.

Activity Classification Using the Genea: Optimum Sampling Frequency and Number of Axes

INTRODUCTION The GENEA shows high accuracy for classification of sedentary, household, walking, and running activities when sampling at 80 Hz on three axes. It is not known whether it is possible to decrease this sampling frequency and/or the number of axes without detriment to classification accuracy. The purpose of this study was to compare the classification rate of activities on the basis of data from a single axis, two axes, and three axes, with sampling rates ranging from 5 to 80 Hz. METHODS Sixty participants (age, 49.4 yr (6.5 yr); BMI, 24.6 kg·m (3.4 kg·m)) completed 10-12 semistructured activities in the laboratory and outdoor environment while wearing a GENEA accelerometer on the right wrist. We analyzed data from single axis, dual axes, and three axes at sampling rates of 5, 10, 20, 40, and 80 Hz. Mathematical models based on features extracted from mean, SD, fast Fourier transform, and wavelet decomposition were built, which combined one of the numbers of axes with one of the sampling rates to classify activities into sedentary, household, walking, and running. RESULTS Classification accuracy was high irrespective of the number of axes for data collected at 80 Hz (96.93% ± 0.97%), 40 Hz (97.4% ± 0.73%), 20 Hz (96.86% ± 1.12%), and 10 Hz (97.01% ± 1.01%) but dropped for data collected at 5 Hz (94.98% ± 1.36%). CONCLUSION Sampling frequencies >10 Hz and/or more than one axis of measurement were not associated with greater classification accuracy. Lower sampling rates and measurement of a single axis would result in a lower data load, longer battery life, and higher efficiency of data processing. Further research should investigate whether a lower sampling rate and a single axis affects classification accuracy when considering a wider range of activities.

Perceived age as a biomarker of ageing: a clinical methodology

In a previous field-based study, how old one looks for one’s age (perceived age) was found to be predictive of mortality in elderly individuals. In conjunction, perceived age is of relevance and interest to the layperson. Here, a clinical methodology for generating perceived age as a biomarker of facial ageing is detailed. The methodology utilises facial photographs of subjects to present images to large numbers of age assessors who are primarily nationals of the country of study origin. In five observational studies in five different countries involving 874 female subjects it was found that subject age and assessor gender, nationality, age and ageing expertise had little effect on the perceived age data generated. However, increasing the numbers of age assessors up to 50 substantially increased the reproducibility of the mean perceived age for an image and a minimum of 10 assessors were required to give reproducible data. This methodology was also compared to a methodology that utilises passport-type photographs of subjects typically taken in field studies. Although the perceived age data from the two types of images were more similar to each other than to chronological age, there was a marked difference between the two sets of data. Therefore, to allow meaningful comparisons across perceived age studies, the same type of image should be used for the generation of perceived age. In conclusion, the methodology detailed here has demonstrated that perceived age can be a reproducible measure when large numbers of adult age assessors are used and can be utilised globally in studies to investigate facial ageing.

Using hypothetical data to assess the effect of numerical format and context on the perception of coronary heart disease risk.

Purpose. To test the hypothesis that responses to coronary heart disease (CHD) risk estimates are heightened by use of ratio formats, peer group risk information, and long time frames. Design. Cross-sectional, experimental, between-factors design. Setting. Three regions in England. Subjects. A total of 740 men and women ages 30 to 70 years. Measures. Risk perception, “emotional” response, intention to change lifestyle. Analysis. Logistic regression was used to investigate the impact of numerical format (ratio vs. percentage), peer group risk (personal vs. peer group), and time frame (10-year vs. 30-year) on risk perception. Analysis of variance was used to investigate the impact of these factors on emotional response and intention to change lifestyle questions. Results. Higher perceived risk was observed when risk was presented as a ratio (p < .001) and when it was supplemented with peer group risk estimates (p = .006). Emotional responses to risk information were heightened when risk was presented as a ratio (p = .0004) and supplemented with peer group risk estimates (p = .002). Presentation with ratios also increased intention to make lifestyle changes (p = .047). Conclusion. Perception of CHD risk information is affected by the presentation format. Where absolute risks may appear low, use of ratios and supplementation of personal risk estimates with peer group risk may increase risk perception.

Facial Appearance Reflects Human Familial Longevity and Cardiovascular Disease Risk in Healthy Individuals

BACKGROUND As facial appearance can be readily quantified and skin tissue easily accessed, they could be valuable tools for determining how biological mechanisms influence tissue degeneration with age and, consequently, human health and lifespan. It is unknown, however, whether appearance reflects disease risk or lifespan independently of factors already known to associate with both health and appearance. METHODS In a cross-sectional study, we compared the amount of skin wrinkling on a sun-protected site (upper inner arm) and the facial appearance of 261 offspring (mean age 63.2 y) of nonagenarian siblings with 253 age-matched controls (mean age 62.7 y), all with no reported disease history. We next examined whether any appearance features that significantly associated with familial longevity also associated with the Framingham cardiovascular disease (CVD) risk score. All analyses were adjusted for chronological age, smoking, photodamage, and body mass index. RESULTS Female and male offspring had reduced upper inner arm skin wrinkling (p = .03 and p < .001, respectively), and the male offspring looked 1.4 y younger than the controls (p = .002). There were no significant associations between CVD risk and upper inner arm skin wrinkling. Women in the lowest quartile of CVD risk looked more than 2 y younger for their age than those in higher risk quartiles (p = .002). Systolic blood pressure was the most significant (p = .004) CVD risk factor that was associated with perceived age in women. CONCLUSIONS Facial appearance and skin wrinkling at a sun-protected site reflect the propensity to reach an extreme old age, and facial appearance reflects the risk of succumbing to CVD independently of chronological age, smoking, photodamage, and BMI.

Exploratory Study of Web-Based Planning and Mobile Text Reminders in an Overweight Population

Background Forming specific health plans can help translate good intentions into action. Mobile text reminders can further enhance the effects of planning on behavior. Objective Our aim was to explore the combined impact of a Web-based, fully automated planning tool and mobile text reminders on intention to change saturated fat intake, self-reported saturated fat intake, and portion size changes over 4 weeks. Methods Of 1013 men and women recruited online, 858 were randomly allocated to 1 of 3 conditions: a planning tool (PT), combined planning tool and text reminders (PTT), and a control group. All outcome measures were assessed by online self-reports. Analysis of covariance was used to analyze the data. Results Participants allocated to the PT (meansat urated fat 3.6, meancopingplanning 3) and PTT (meansaturatedfat 3.5, meancopingplanning 3.1) reported a lower consumption of high-fat foods (F 2,571 = 4.74, P = .009) and higher levels of coping planning (F 2,571 = 7.22, P < .001) than the control group (meansat urated f at 3.9, meancopingplanning 2.8). Participants in the PTT condition also reported smaller portion sizes of high-fat foods (mean 2.8; F 2, 569 = 4.12, P = .0) than the control group (meanportions 3.1). The reduction in portion size was driven primarily by the male participants in the PTT (P = .003). We found no significant group differences in terms of percentage saturated fat intake, intentions, action planning, self-efficacy, or feedback on the intervention. Conclusions These findings support the use of Web-based tools and mobile technologies to change dietary behavior. The combination of a fully automated Web-based planning tool with mobile text reminders led to lower self-reported consumption of high-fat foods and greater reductions in portion sizes than in a control condition. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 61819220; http://www.controlled-trials.com/ISRCTN61819220 (Archived by WebCite at http://www.webcitation.org/63YiSy6R8)

A sequential two meal challenge reveals abnormalities in postprandial TAG but not glucose in men with increasing numbers of metabolic syndrome components

OBJECTIVE To examine the impact of increasing numbers of metabolic syndrome (MetS) components on postprandial lipaemia. METHODS Healthy men (n=112) underwent a sequential meal postprandial investigation, in which blood samples were taken at regular intervals after a test breakfast (0min) and lunch (330min). Lipids, glucose and insulin were measured in the fasting sample, with triacylglycerol (TAG), non-esterified fatty acids and glucose analysed in the postprandial samples. RESULTS Subjects were grouped according to the number of MetS components regardless of the combinations of components (0/1, 2, 3 and 4/5). As expected, there was a trend for an increase in body mass index, blood pressure, fasting TAG, glucose and insulin, and a decrease in fasting high-density lipoprotein cholesterol with increasing numbers of MetS components (P≤0.0004). A similar trend was observed for the summary measures of the postprandial TAG and glucose responses. For TAG, the area under the curve (AUC) and maximum concentration (maxC) were significantly greater in men with ≥3 than <3 components (P<0.001), whereas incremental AUC was greater in those with 3 than 0/1 and 2, and 4/5 compared with 2 components (P<0.04). For glucose, maxC after the test breakfast (0-330min) and total AUC (0-480min) were higher in men with ≥3 than <3 components (P≤0.001). CONCLUSIONS Our data analysis has revealed a linear trend between increasing numbers of MetS components and magnitude (AUC) of the postprandial TAG and glucose responses. Furthermore, the two meal challenge discriminated a worsening of postprandial lipaemic control in subjects with ≥3 MetS components.