Exploration of Confounding Due to Poor Health in an Accelerometer-Mortality Study.

PURPOSE: Confounding due to poor health is a concern in accelerometer-based studies of physical activity and health, but detailed investigations of this source of bias are lacking. METHODS: US adults (n = 4840) from the National Health and Nutrition Examination Survey (2003 to 2006) wore an accelerometer for 1 to 7 d (mean = 5.7 d) and were followed for mortality through 2015. Logistic regression was used to examine odds ratios between poor health (chronic conditions, self-reported health, mobility limitations, frailty) and low physical activity levels; Cox models were used to estimate adjusted hazard ratios (HR) and 95% CI for mortality associations for a 1 h·d increase in moderate-to-vigorous-intensity physical activity (MVPA) using two commonly used cut-points (MVPA760, MVPA2020). Modeling scenarios with shorter and longer follow-up time, increasing adjustment for poor health, by age group, and after excluding early years of follow-up were used to assess bias. RESULTS: Over a mean of 10.1 yr of follow-up, 1165 deaths occurred. Poor health was associated with low MVPA760 levels and increased mortality risk. In fully adjusted MVPA760 models, HR was 26% stronger comparing 0 to 4 yr (HR = 0.46) with 0 to 12 yr of follow-up (HR = 0.62), particularly in older adults (65 yr and older). Increasing statistical adjustment for poor health attenuated MVPA760 associations by 13% to 15%, and exclusion of the first 2 yr of follow-up had limited effects. Comparable results were obtained with the MVPA2020 cut-point. CONCLUSIONS: We did not find evidence that confounding by health status resulted in entirely spurious MVPA-mortality associations; however, potential bias was appreciable in modeling scenarios involving shorter follow-up (<6 yr), older adults, and more limited statistical adjustment for poor health. The strength of MVPA-mortality associations in studies reflecting these scenarios should be interpreted cautiously.

Does total volume of physical activity matter more than pattern for onset of CVD? A prospective cohort study of older British men.

AIMS: With increasing age, physical inactivity and sedentary behaviour levels increase, as does cardiovascular disease (CVD) incidence. We investigate how device-measured sedentary behaviour and physical activity (PA) are related to CVD onset in men aged 70+; whether the total volume of activity is more important than pattern. METHODS AND RESULTS: Prospective population-based cohort study of men recruited from 24 UK General Practices in 1978-80. In 2010-12, 3137 survivors were invited to complete questionnaires and wear an Actigraph GT3x accelerometer for 7 days. PA intensity was categorised as sedentary, light and moderate to vigorous (MVPA). Men were followed up for Myocardial Infarction, stroke and heart failure (ICD9 410-414, 430-438 and 428) morbidity and mortality from 2010 to 12 to June 2016. Hazard Ratios (HRs) for incident Cardiovascular Disease (CVD) were estimated. 1528/3137 (49%) men had sufficient accelerometer data. 254 men with pre-existing CVD were excluded. Participants' mean age was 78.4 (range 71-92) years. After median 4.9 years follow-up, 122 first CVD events occurred in 1181 men (22.7/1000 person-years) with complete data. For each additional 30 min in sedentary behaviour, light PA,10 min in MVPA, or 1000 steps/day, HRs for CVD were 1.09(95%CI 1.00, 1.19), 0.94(0.85, 1.04), 0.88(0.81, 0.96) and 0.86(0.78 to 0.95) respectively, adjusted for measurement-related factors, socio-demographics, health behaviours and disability. HRs for accumulating 150 min/week MVPA in bouts ≥1 min and bouts ≥10 min were 0.47(0.32 to 0.69), and 0.49(0.25, 0.98). CONCLUSIONS: In older men, high volume of steps or MVPA rather than MVPA bouts was associated with reduced CVD risk.

A new method to estimate the real upper limit of the false alarm rate in a 3 accelerometry-based fall detector for the elderly.

Falls are a major concern for the elderly and their ability to remain healthy. Fall detection systems may notify emergency responders when no one apart from the injured is present. However, their real-world application is limited by a number of factors such as high false positive rates, low-compliance, poor-usability and short battery lifetime. In order to improve these aspects we have developed a miniaturized 3D accelerometer integrated in a belt buckle, the actibelt(®), and a fall detection algorithm. We have used a new evaluation method to assess the upper limit of the false alarm rate of our algorithm using a large set of long term standardized acceleration measurements recorded under real life conditions. Our algorithm has a false alarm rate of seventeen false alarms per month and has the potential to be reduced down to at most three false alarms per month when activities which require the sensor to be removed are eliminated. In laboratory settings, the algorithm has a sensitivity of 100%. The algorithm was sucessfully validated using data from a real-world fall.